id	sid	tid	token	lemma	pos
fcis-2135	1	1	frontiers	frontier	NOUN
fcis-2135	1	2	in	in	ADP
fcis-2135	1	3	computing	computing	NOUN
fcis-2135	1	4	and	and	CCONJ
fcis-2135	1	5	intelligent	intelligent	ADJ
fcis-2135	1	6	systems	system	NOUN
fcis-2135	1	7	issn	issn	VERB
fcis-2135	1	8	:	:	PUNCT
fcis-2135	1	9	2832	2832	NUM
fcis-2135	1	10	-	-	SYM
fcis-2135	1	11	6024	6024	NUM
fcis-2135	1	12	|	|	NOUN
fcis-2135	1	13	vol	vol	NOUN
fcis-2135	1	14	.	.	PROPN
fcis-2135	2	1	1	1	NUM
fcis-2135	2	2	,	,	PUNCT
fcis-2135	2	3	no	no	INTJ
fcis-2135	2	4	.	.	NOUN
fcis-2135	2	5	3	3	NUM
fcis-2135	2	6	,	,	PUNCT
fcis-2135	2	7	2022	2022	NUM
fcis-2135	2	8	68	68	NUM
fcis-2135	2	9	review	review	NOUN
fcis-2135	2	10	of	of	ADP
fcis-2135	2	11	pedestrian	pedestrian	NOUN
fcis-2135	2	12	trajectory	trajectory	NOUN
fcis-2135	2	13	prediction	prediction	NOUN
fcis-2135	2	14	methods	method	NOUN
fcis-2135	2	15	xiaochuan	xiaochuan	PROPN
fcis-2135	2	16	tan	tan	PROPN
fcis-2135	2	17	*	*	PROPN
fcis-2135	2	18	,	,	PUNCT
fcis-2135	2	19	ruiyuan	ruiyuan	PROPN
fcis-2135	2	20	liu	liu	PROPN
fcis-2135	2	21	,	,	PUNCT
fcis-2135	2	22	shuai	shuai	PROPN
fcis-2135	2	23	zhang	zhang	PROPN
fcis-2135	2	24	,	,	PUNCT
fcis-2135	2	25	jiaojiao	jiaojiao	PROPN
fcis-2135	2	26	li	li	PROPN
fcis-2135	2	27	,	,	PUNCT
fcis-2135	2	28	pengcheng	pengcheng	PROPN
fcis-2135	2	29	ma	ma	PROPN
fcis-2135	2	30	school	school	PROPN
fcis-2135	2	31	of	of	ADP
fcis-2135	2	32	transportation	transportation	NOUN
fcis-2135	2	33	and	and	CCONJ
fcis-2135	2	34	vehicle	vehicle	NOUN
fcis-2135	2	35	engineering	engineering	NOUN
fcis-2135	2	36	,	,	PUNCT
fcis-2135	2	37	shandong	shandong	PROPN
fcis-2135	2	38	university	university	PROPN
fcis-2135	2	39	of	of	ADP
fcis-2135	2	40	technology	technology	PROPN
fcis-2135	2	41	,	,	PUNCT
fcis-2135	2	42	zibo	zibo	PROPN
fcis-2135	2	43	255000	255000	NUM
fcis-2135	2	44	,	,	PUNCT
fcis-2135	2	45	china	china	PROPN
fcis-2135	2	46	.	.	PUNCT
fcis-2135	3	1	*	*	PUNCT
fcis-2135	3	2	corresponding	correspond	VERB
fcis-2135	3	3	author	author	NOUN
fcis-2135	3	4	:	:	PUNCT
fcis-2135	3	5	xiaochuan	xiaochuan	PROPN
fcis-2135	3	6	tan	tan	PROPN
fcis-2135	3	7	(	(	PUNCT
fcis-2135	3	8	email	email	NOUN
fcis-2135	3	9	:	:	PUNCT
fcis-2135	3	10	915486554@qq.com	915486554@qq.com	NUM
fcis-2135	3	11	)	)	PUNCT
fcis-2135	3	12	abstract	abstract	NOUN
fcis-2135	3	13	:	:	PUNCT
fcis-2135	3	14	urban	urban	ADJ
fcis-2135	3	15	driverless	driverless	NOUN
fcis-2135	3	16	vehicles	vehicle	NOUN
fcis-2135	3	17	will	will	AUX
fcis-2135	3	18	inevitably	inevitably	ADV
fcis-2135	3	19	interact	interact	VERB
fcis-2135	3	20	with	with	ADP
fcis-2135	3	21	pedestrians	pedestrian	NOUN
fcis-2135	3	22	in	in	ADP
fcis-2135	3	23	the	the	DET
fcis-2135	3	24	process	process	NOUN
fcis-2135	3	25	of	of	ADP
fcis-2135	3	26	driving	drive	VERB
fcis-2135	3	27	.	.	PUNCT
fcis-2135	4	1	in	in	ADP
fcis-2135	4	2	order	order	NOUN
fcis-2135	4	3	to	to	PART
fcis-2135	4	4	avoid	avoid	VERB
fcis-2135	4	5	path	path	NOUN
fcis-2135	4	6	conflict	conflict	NOUN
fcis-2135	4	7	with	with	ADP
fcis-2135	4	8	pedestrians	pedestrian	NOUN
fcis-2135	4	9	,	,	PUNCT
fcis-2135	4	10	the	the	DET
fcis-2135	4	11	research	research	NOUN
fcis-2135	4	12	on	on	ADP
fcis-2135	4	13	pedestrian	pedestrian	NOUN
fcis-2135	4	14	trajectory	trajectory	NOUN
fcis-2135	4	15	prediction	prediction	NOUN
fcis-2135	4	16	is	be	AUX
fcis-2135	4	17	of	of	ADP
fcis-2135	4	18	great	great	ADJ
fcis-2135	4	19	significance	significance	NOUN
fcis-2135	4	20	.	.	PUNCT
fcis-2135	5	1	this	this	DET
fcis-2135	5	2	paper	paper	NOUN
fcis-2135	5	3	mainly	mainly	ADV
fcis-2135	5	4	summarizes	summarize	VERB
fcis-2135	5	5	the	the	DET
fcis-2135	5	6	technical	technical	ADJ
fcis-2135	5	7	classification	classification	NOUN
fcis-2135	5	8	and	and	CCONJ
fcis-2135	5	9	research	research	NOUN
fcis-2135	5	10	status	status	NOUN
fcis-2135	5	11	of	of	ADP
fcis-2135	5	12	pedestrian	pedestrian	NOUN
fcis-2135	5	13	trajectory	trajectory	NOUN
fcis-2135	5	14	prediction	prediction	NOUN
fcis-2135	5	15	at	at	ADP
fcis-2135	5	16	this	this	DET
fcis-2135	5	17	stage	stage	NOUN
fcis-2135	5	18	in	in	ADP
fcis-2135	5	19	detail	detail	NOUN
fcis-2135	5	20	.	.	PUNCT
fcis-2135	6	1	according	accord	VERB
fcis-2135	6	2	to	to	ADP
fcis-2135	6	3	the	the	DET
fcis-2135	6	4	different	different	ADJ
fcis-2135	6	5	modeling	modeling	NOUN
fcis-2135	6	6	methods	method	NOUN
fcis-2135	6	7	,	,	PUNCT
fcis-2135	6	8	the	the	DET
fcis-2135	6	9	existing	exist	VERB
fcis-2135	6	10	trajectory	trajectory	NOUN
fcis-2135	6	11	prediction	prediction	NOUN
fcis-2135	6	12	methods	method	NOUN
fcis-2135	6	13	are	be	AUX
fcis-2135	6	14	divided	divide	VERB
fcis-2135	6	15	into	into	ADP
fcis-2135	6	16	shallow	shallow	ADJ
fcis-2135	6	17	learning	learning	NOUN
fcis-2135	6	18	-	-	PUNCT
fcis-2135	6	19	based	base	VERB
fcis-2135	6	20	trajectory	trajectory	NOUN
fcis-2135	6	21	prediction	prediction	NOUN
fcis-2135	6	22	methods	method	NOUN
fcis-2135	6	23	and	and	CCONJ
fcis-2135	6	24	depth	depth	NOUN
fcis-2135	6	25	learning	learning	NOUN
fcis-2135	6	26	based	base	VERB
fcis-2135	6	27	trajectory	trajectory	NOUN
fcis-2135	6	28	prediction	prediction	NOUN
fcis-2135	6	29	methods	method	NOUN
fcis-2135	6	30	.	.	PUNCT
fcis-2135	7	1	the	the	DET
fcis-2135	7	2	advantages	advantage	NOUN
fcis-2135	7	3	and	and	CCONJ
fcis-2135	7	4	disadvantages	disadvantage	NOUN
fcis-2135	7	5	of	of	ADP
fcis-2135	7	6	the	the	DET
fcis-2135	7	7	depth	depth	NOUN
fcis-2135	7	8	learning	learning	NOUN
fcis-2135	7	9	based	base	VERB
fcis-2135	7	10	trajectory	trajectory	NOUN
fcis-2135	7	11	prediction	prediction	NOUN
fcis-2135	7	12	methods	method	NOUN
fcis-2135	7	13	are	be	AUX
fcis-2135	7	14	compared	compare	VERB
fcis-2135	7	15	,	,	PUNCT
fcis-2135	7	16	and	and	CCONJ
fcis-2135	7	17	the	the	DET
fcis-2135	7	18	current	current	ADJ
fcis-2135	7	19	mainstream	mainstream	NOUN
fcis-2135	7	20	pedestrian	pedestrian	NOUN
fcis-2135	7	21	trajectory	trajectory	NOUN
fcis-2135	7	22	prediction	prediction	NOUN
fcis-2135	7	23	public	public	ADJ
fcis-2135	7	24	dataset	dataset	NOUN
fcis-2135	7	25	is	be	AUX
fcis-2135	7	26	summarized	summarize	VERB
fcis-2135	7	27	,	,	PUNCT
fcis-2135	7	28	and	and	CCONJ
fcis-2135	7	29	the	the	DET
fcis-2135	7	30	performance	performance	NOUN
fcis-2135	7	31	of	of	ADP
fcis-2135	7	32	the	the	DET
fcis-2135	7	33	mainstream	mainstream	NOUN
fcis-2135	7	34	pedestrian	pedestrian	NOUN
fcis-2135	7	35	trajectory	trajectory	NOUN
fcis-2135	7	36	prediction	prediction	NOUN
fcis-2135	7	37	methods	method	NOUN
fcis-2135	7	38	is	be	AUX
fcis-2135	7	39	compared	compare	VERB
fcis-2135	7	40	in	in	ADP
fcis-2135	7	41	the	the	DET
fcis-2135	7	42	dataset	dataset	NOUN
fcis-2135	7	43	.	.	PUNCT
fcis-2135	8	1	finally	finally	ADV
fcis-2135	8	2	,	,	PUNCT
fcis-2135	8	3	the	the	DET
fcis-2135	8	4	challenges	challenge	NOUN
fcis-2135	8	5	and	and	CCONJ
fcis-2135	8	6	development	development	NOUN
fcis-2135	8	7	trend	trend	NOUN
fcis-2135	8	8	of	of	ADP
fcis-2135	8	9	pedestrian	pedestrian	NOUN
fcis-2135	8	10	trajectory	trajectory	NOUN
fcis-2135	8	11	prediction	prediction	NOUN
fcis-2135	8	12	at	at	ADP
fcis-2135	8	13	this	this	DET
fcis-2135	8	14	stage	stage	NOUN
fcis-2135	8	15	are	be	AUX
fcis-2135	8	16	prospected	prospect	VERB
fcis-2135	8	17	.	.	PUNCT
fcis-2135	9	1	keywords	keyword	NOUN
fcis-2135	9	2	:	:	PUNCT
fcis-2135	9	3	pedestrian	pedestrian	NOUN
fcis-2135	9	4	trajectory	trajectory	NOUN
fcis-2135	9	5	prediction	prediction	NOUN
fcis-2135	9	6	;	;	PUNCT
fcis-2135	9	7	automatic	automatic	ADJ
fcis-2135	9	8	driving	driving	NOUN
fcis-2135	9	9	;	;	PUNCT
fcis-2135	9	10	deep	deep	ADJ
fcis-2135	9	11	learning	learning	NOUN
fcis-2135	9	12	;	;	PUNCT
fcis-2135	9	13	prediction	prediction	NOUN
fcis-2135	9	14	method	method	NOUN
fcis-2135	9	15	;	;	PUNCT
fcis-2135	9	16	neural	neural	ADJ
fcis-2135	9	17	network	network	NOUN
fcis-2135	9	18	.	.	PUNCT
fcis-2135	10	1	1	1	X
fcis-2135	10	2	.	.	X
fcis-2135	10	3	introduction	introduction	NOUN
fcis-2135	10	4	with	with	ADP
fcis-2135	10	5	the	the	DET
fcis-2135	10	6	rapid	rapid	ADJ
fcis-2135	10	7	development	development	NOUN
fcis-2135	10	8	of	of	ADP
fcis-2135	10	9	the	the	DET
fcis-2135	10	10	global	global	ADJ
fcis-2135	10	11	economy	economy	NOUN
fcis-2135	10	12	and	and	CCONJ
fcis-2135	10	13	the	the	DET
fcis-2135	10	14	acceleration	acceleration	NOUN
fcis-2135	10	15	of	of	ADP
fcis-2135	10	16	urban	urban	ADJ
fcis-2135	10	17	processes	process	NOUN
fcis-2135	10	18	,	,	PUNCT
fcis-2135	10	19	the	the	DET
fcis-2135	10	20	global	global	ADJ
fcis-2135	10	21	automotive	automotive	ADJ
fcis-2135	10	22	industry	industry	NOUN
fcis-2135	10	23	is	be	AUX
fcis-2135	10	24	developing	develop	VERB
fcis-2135	10	25	rapidly	rapidly	ADV
fcis-2135	10	26	.	.	PUNCT
fcis-2135	11	1	global	global	ADJ
fcis-2135	11	2	car	car	NOUN
fcis-2135	11	3	ownership	ownership	NOUN
fcis-2135	11	4	is	be	AUX
fcis-2135	11	5	expected	expect	VERB
fcis-2135	11	6	to	to	PART
fcis-2135	11	7	reach	reach	VERB
fcis-2135	11	8	2.5	2.5	NUM
fcis-2135	11	9	billion	billion	NUM
fcis-2135	11	10	vehicles	vehicle	NOUN
fcis-2135	11	11	by	by	ADP
fcis-2135	11	12	2050	2050	NUM
fcis-2135	11	13	.	.	PUNCT
fcis-2135	12	1	the	the	DET
fcis-2135	12	2	popularity	popularity	NOUN
fcis-2135	12	3	of	of	ADP
fcis-2135	12	4	automobiles	automobile	NOUN
fcis-2135	12	5	brings	bring	VERB
fcis-2135	12	6	convenience	convenience	NOUN
fcis-2135	12	7	to	to	ADP
fcis-2135	12	8	people	people	NOUN
fcis-2135	12	9	's	's	PART
fcis-2135	12	10	lives	life	NOUN
fcis-2135	12	11	.	.	PUNCT
fcis-2135	13	1	at	at	ADP
fcis-2135	13	2	the	the	DET
fcis-2135	13	3	same	same	ADJ
fcis-2135	13	4	time	time	NOUN
fcis-2135	13	5	,	,	PUNCT
fcis-2135	13	6	traffic	traffic	NOUN
fcis-2135	13	7	congestion	congestion	NOUN
fcis-2135	13	8	and	and	CCONJ
fcis-2135	13	9	frequent	frequent	ADJ
fcis-2135	13	10	traffic	traffic	NOUN
fcis-2135	13	11	accidents	accident	NOUN
fcis-2135	13	12	are	be	AUX
fcis-2135	13	13	also	also	ADV
fcis-2135	13	14	increasing	increase	VERB
fcis-2135	13	15	,	,	PUNCT
fcis-2135	13	16	which	which	PRON
fcis-2135	13	17	brings	bring	VERB
fcis-2135	13	18	great	great	ADJ
fcis-2135	13	19	hidden	hide	VERB
fcis-2135	13	20	dangers	danger	NOUN
fcis-2135	13	21	to	to	ADP
fcis-2135	13	22	driving	drive	VERB
fcis-2135	13	23	safety	safety	NOUN
fcis-2135	13	24	.	.	PUNCT
fcis-2135	14	1	pedestrians	pedestrian	NOUN
fcis-2135	14	2	and	and	CCONJ
fcis-2135	14	3	cyclists	cyclist	NOUN
fcis-2135	14	4	,	,	PUNCT
fcis-2135	14	5	as	as	ADP
fcis-2135	14	6	vulnerable	vulnerable	ADJ
fcis-2135	14	7	groups	group	NOUN
fcis-2135	14	8	among	among	ADP
fcis-2135	14	9	road	road	NOUN
fcis-2135	14	10	traffic	traffic	NOUN
fcis-2135	14	11	participants	participant	NOUN
fcis-2135	14	12	,	,	PUNCT
fcis-2135	14	13	are	be	AUX
fcis-2135	14	14	extremely	extremely	ADV
fcis-2135	14	15	vulnerable	vulnerable	ADJ
fcis-2135	14	16	without	without	ADP
fcis-2135	14	17	any	any	DET
fcis-2135	14	18	safety	safety	NOUN
fcis-2135	14	19	protection	protection	NOUN
fcis-2135	14	20	devices	device	NOUN
fcis-2135	14	21	when	when	SCONJ
fcis-2135	14	22	participating	participate	VERB
fcis-2135	14	23	in	in	ADP
fcis-2135	14	24	traffic	traffic	NOUN
fcis-2135	14	25	activities	activity	NOUN
fcis-2135	14	26	.	.	PUNCT
fcis-2135	15	1	according	accord	VERB
fcis-2135	15	2	to	to	ADP
fcis-2135	15	3	the	the	DET
fcis-2135	15	4	data	datum	NOUN
fcis-2135	15	5	of	of	ADP
fcis-2135	15	6	china	china	PROPN
fcis-2135	15	7	's	's	PART
fcis-2135	15	8	national	national	PROPN
fcis-2135	15	9	bureau	bureau	PROPN
fcis-2135	15	10	of	of	ADP
fcis-2135	15	11	statistics	statistic	NOUN
fcis-2135	15	12	,	,	PUNCT
fcis-2135	15	13	the	the	DET
fcis-2135	15	14	number	number	NOUN
fcis-2135	15	15	of	of	ADP
fcis-2135	15	16	road	road	NOUN
fcis-2135	15	17	vulnerable	vulnerable	ADJ
fcis-2135	15	18	groups	group	NOUN
fcis-2135	15	19	killed	kill	VERB
fcis-2135	15	20	by	by	ADP
fcis-2135	15	21	traffic	traffic	NOUN
fcis-2135	15	22	accidents	accident	NOUN
fcis-2135	15	23	in	in	ADP
fcis-2135	15	24	china	china	PROPN
fcis-2135	15	25	accounts	account	VERB
fcis-2135	15	26	for	for	ADP
fcis-2135	15	27	26	26	NUM
fcis-2135	15	28	%	%	NOUN
fcis-2135	15	29	of	of	ADP
fcis-2135	15	30	the	the	DET
fcis-2135	15	31	total	total	ADJ
fcis-2135	15	32	number	number	NOUN
fcis-2135	15	33	of	of	ADP
fcis-2135	15	34	accidents	accident	NOUN
fcis-2135	15	35	every	every	DET
fcis-2135	15	36	year	year	NOUN
fcis-2135	15	37	.	.	PUNCT
fcis-2135	16	1	therefore	therefore	ADV
fcis-2135	16	2	,	,	PUNCT
fcis-2135	16	3	to	to	PART
fcis-2135	16	4	further	far	ADV
fcis-2135	16	5	enhance	enhance	VERB
fcis-2135	16	6	road	road	NOUN
fcis-2135	16	7	traffic	traffic	NOUN
fcis-2135	16	8	safety	safety	NOUN
fcis-2135	16	9	and	and	CCONJ
fcis-2135	16	10	pedestrian	pedestrian	NOUN
fcis-2135	16	11	safety	safety	NOUN
fcis-2135	16	12	,	,	PUNCT
fcis-2135	16	13	reduce	reduce	VERB
fcis-2135	16	14	casualties	casualty	NOUN
fcis-2135	16	15	and	and	CCONJ
fcis-2135	16	16	property	property	NOUN
fcis-2135	16	17	losses	loss	NOUN
fcis-2135	16	18	is	be	AUX
fcis-2135	16	19	the	the	DET
fcis-2135	16	20	future	future	NOUN
fcis-2135	16	21	we	we	PRON
fcis-2135	16	22	need	need	VERB
fcis-2135	16	23	to	to	PART
fcis-2135	16	24	solve	solve	VERB
fcis-2135	16	25	the	the	DET
fcis-2135	16	26	problem	problem	NOUN
fcis-2135	16	27	.	.	PUNCT
fcis-2135	17	1	among	among	ADP
fcis-2135	17	2	them	they	PRON
fcis-2135	17	3	,	,	PUNCT
fcis-2135	17	4	improving	improve	VERB
fcis-2135	17	5	the	the	DET
fcis-2135	17	6	trajectory	trajectory	NOUN
fcis-2135	17	7	prediction	prediction	NOUN
fcis-2135	17	8	of	of	ADP
fcis-2135	17	9	pedestrians	pedestrian	NOUN
fcis-2135	17	10	crossing	cross	VERB
fcis-2135	17	11	the	the	DET
fcis-2135	17	12	street	street	NOUN
fcis-2135	17	13	by	by	ADP
fcis-2135	17	14	autonomous	autonomous	ADJ
fcis-2135	17	15	vehicles	vehicle	NOUN
fcis-2135	17	16	is	be	AUX
fcis-2135	17	17	an	an	DET
fcis-2135	17	18	important	important	ADJ
fcis-2135	17	19	measure	measure	NOUN
fcis-2135	17	20	to	to	PART
fcis-2135	17	21	avoid	avoid	VERB
fcis-2135	17	22	traffic	traffic	NOUN
fcis-2135	17	23	accidents	accident	NOUN
fcis-2135	17	24	.	.	PUNCT
fcis-2135	18	1	understanding	understand	VERB
fcis-2135	18	2	human	human	ADJ
fcis-2135	18	3	motion	motion	NOUN
fcis-2135	18	4	is	be	AUX
fcis-2135	18	5	a	a	DET
fcis-2135	18	6	key	key	ADJ
fcis-2135	18	7	skill	skill	NOUN
fcis-2135	18	8	for	for	ADP
fcis-2135	18	9	the	the	DET
fcis-2135	18	10	coexistence	coexistence	NOUN
fcis-2135	18	11	and	and	CCONJ
fcis-2135	18	12	interaction	interaction	NOUN
fcis-2135	18	13	between	between	ADP
fcis-2135	18	14	intelligent	intelligent	ADJ
fcis-2135	18	15	systems	system	NOUN
fcis-2135	18	16	and	and	CCONJ
fcis-2135	18	17	humans	human	NOUN
fcis-2135	18	18	,	,	PUNCT
fcis-2135	18	19	which	which	PRON
fcis-2135	18	20	involves	involve	VERB
fcis-2135	18	21	representation	representation	NOUN
fcis-2135	18	22	,	,	PUNCT
fcis-2135	18	23	perception	perception	NOUN
fcis-2135	18	24	and	and	CCONJ
fcis-2135	18	25	motion	motion	NOUN
fcis-2135	18	26	analysis	analysis	NOUN
fcis-2135	18	27	.	.	PUNCT
fcis-2135	19	1	prediction	prediction	NOUN
fcis-2135	19	2	plays	play	VERB
fcis-2135	19	3	an	an	DET
fcis-2135	19	4	important	important	ADJ
fcis-2135	19	5	role	role	NOUN
fcis-2135	19	6	in	in	ADP
fcis-2135	19	7	human	human	ADJ
fcis-2135	19	8	motion	motion	NOUN
fcis-2135	19	9	analysis	analysis	NOUN
fcis-2135	19	10	.	.	PUNCT
fcis-2135	20	1	as	as	SCONJ
fcis-2135	20	2	time	time	NOUN
fcis-2135	20	3	goes	go	VERB
fcis-2135	20	4	by	by	ADV
fcis-2135	20	5	,	,	PUNCT
fcis-2135	20	6	the	the	DET
fcis-2135	20	7	model	model	NOUN
fcis-2135	20	8	can	can	AUX
fcis-2135	20	9	predict	predict	VERB
fcis-2135	20	10	scenes	scene	NOUN
fcis-2135	20	11	involving	involve	VERB
fcis-2135	20	12	multiple	multiple	ADJ
fcis-2135	20	13	agents	agent	NOUN
fcis-2135	20	14	and	and	CCONJ
fcis-2135	20	15	integrate	integrate	VERB
fcis-2135	20	16	this	this	DET
fcis-2135	20	17	scene	scene	NOUN
fcis-2135	20	18	information	information	NOUN
fcis-2135	20	19	in	in	ADP
fcis-2135	20	20	an	an	DET
fcis-2135	20	21	active	active	ADJ
fcis-2135	20	22	way	way	NOUN
fcis-2135	20	23	,	,	PUNCT
fcis-2135	20	24	that	that	ADV
fcis-2135	20	25	is	is	ADV
fcis-2135	20	26	,	,	PUNCT
fcis-2135	20	27	to	to	PART
fcis-2135	20	28	enhance	enhance	VERB
fcis-2135	20	29	the	the	DET
fcis-2135	20	30	effects	effect	NOUN
fcis-2135	20	31	of	of	ADP
fcis-2135	20	32	active	active	ADJ
fcis-2135	20	33	perception	perception	NOUN
fcis-2135	20	34	,	,	PUNCT
fcis-2135	20	35	predictive	predictive	ADJ
fcis-2135	20	36	planning	planning	NOUN
fcis-2135	20	37	,	,	PUNCT
fcis-2135	20	38	model	model	NOUN
fcis-2135	20	39	predictive	predictive	ADJ
fcis-2135	20	40	control	control	NOUN
fcis-2135	20	41	or	or	CCONJ
fcis-2135	20	42	human	human	ADJ
fcis-2135	20	43	-	-	PUNCT
fcis-2135	20	44	computer	computer	NOUN
fcis-2135	20	45	interaction	interaction	NOUN
fcis-2135	20	46	.	.	PUNCT
fcis-2135	21	1	therefore	therefore	ADV
fcis-2135	21	2	,	,	PUNCT
fcis-2135	21	3	in	in	ADP
fcis-2135	21	4	recent	recent	ADJ
fcis-2135	21	5	years	year	NOUN
fcis-2135	21	6	,	,	PUNCT
fcis-2135	21	7	pedestrian	pedestrian	NOUN
fcis-2135	21	8	trajectory	trajectory	NOUN
fcis-2135	21	9	prediction	prediction	NOUN
fcis-2135	21	10	has	have	AUX
fcis-2135	21	11	been	be	AUX
fcis-2135	21	12	the	the	DET
fcis-2135	21	13	focus	focus	NOUN
fcis-2135	21	14	of	of	ADP
fcis-2135	21	15	research	research	NOUN
fcis-2135	21	16	in	in	ADP
fcis-2135	21	17	many	many	ADJ
fcis-2135	21	18	fields	field	NOUN
fcis-2135	21	19	,	,	PUNCT
fcis-2135	21	20	such	such	ADJ
fcis-2135	21	21	as	as	ADP
fcis-2135	21	22	autonomous	autonomous	ADJ
fcis-2135	21	23	vehicles	vehicle	NOUN
fcis-2135	21	24	,	,	PUNCT
fcis-2135	21	25	service	service	NOUN
fcis-2135	21	26	robots	robot	NOUN
fcis-2135	21	27	,	,	PUNCT
fcis-2135	21	28	intelligent	intelligent	ADJ
fcis-2135	21	29	transportation	transportation	NOUN
fcis-2135	21	30	,	,	PUNCT
fcis-2135	21	31	command	command	NOUN
fcis-2135	21	32	cities	city	NOUN
fcis-2135	21	33	,	,	PUNCT
fcis-2135	21	34	etc	etc	X
fcis-2135	21	35	.	.	X
fcis-2135	21	36	ensuring	ensure	VERB
fcis-2135	21	37	the	the	DET
fcis-2135	21	38	safety	safety	NOUN
fcis-2135	21	39	of	of	ADP
fcis-2135	21	40	road	road	NOUN
fcis-2135	21	41	users	user	NOUN
fcis-2135	21	42	in	in	ADP
fcis-2135	21	43	traffic	traffic	NOUN
fcis-2135	21	44	scenarios	scenario	NOUN
fcis-2135	21	45	is	be	AUX
fcis-2135	21	46	a	a	DET
fcis-2135	21	47	prerequisite	prerequisite	NOUN
fcis-2135	21	48	for	for	ADP
fcis-2135	21	49	the	the	DET
fcis-2135	21	50	widespread	widespread	ADJ
fcis-2135	21	51	use	use	NOUN
fcis-2135	21	52	of	of	ADP
fcis-2135	21	53	autonomous	autonomous	ADJ
fcis-2135	21	54	vehicles	vehicle	NOUN
fcis-2135	21	55	[	[	X
fcis-2135	21	56	1	1	NUM
fcis-2135	21	57	]	]	PUNCT
fcis-2135	21	58	.	.	PUNCT
fcis-2135	22	1	if	if	SCONJ
fcis-2135	22	2	the	the	DET
fcis-2135	22	3	autonomous	autonomous	ADJ
fcis-2135	22	4	vehicle	vehicle	NOUN
fcis-2135	22	5	can	can	AUX
fcis-2135	22	6	accurately	accurately	ADV
fcis-2135	22	7	predict	predict	VERB
fcis-2135	22	8	the	the	DET
fcis-2135	22	9	location	location	NOUN
fcis-2135	22	10	of	of	ADP
fcis-2135	22	11	the	the	DET
fcis-2135	22	12	surrounding	surround	VERB
fcis-2135	22	13	pedestrians	pedestrian	NOUN
fcis-2135	22	14	in	in	ADP
fcis-2135	22	15	the	the	DET
fcis-2135	22	16	traffic	traffic	NOUN
fcis-2135	22	17	scene	scene	NOUN
fcis-2135	22	18	,	,	PUNCT
fcis-2135	22	19	it	it	PRON
fcis-2135	22	20	can	can	AUX
fcis-2135	22	21	avoid	avoid	VERB
fcis-2135	22	22	traffic	traffic	NOUN
fcis-2135	22	23	accidents	accident	NOUN
fcis-2135	22	24	and	and	CCONJ
fcis-2135	22	25	ensure	ensure	VERB
fcis-2135	22	26	pedestrian	pedestrian	NOUN
fcis-2135	22	27	safety	safety	NOUN
fcis-2135	22	28	.	.	PUNCT
fcis-2135	23	1	at	at	ADP
fcis-2135	23	2	present	present	ADJ
fcis-2135	23	3	,	,	PUNCT
fcis-2135	23	4	there	there	PRON
fcis-2135	23	5	are	be	VERB
fcis-2135	23	6	three	three	NUM
fcis-2135	23	7	main	main	ADJ
fcis-2135	23	8	difficulties	difficulty	NOUN
fcis-2135	23	9	in	in	ADP
fcis-2135	23	10	pedestrian	pedestrian	NOUN
fcis-2135	23	11	crossing	crossing	NOUN
fcis-2135	23	12	trajectory	trajectory	NOUN
fcis-2135	23	13	prediction	prediction	NOUN
fcis-2135	23	14	.	.	PUNCT
fcis-2135	24	1	(	(	PUNCT
fcis-2135	24	2	1	1	X
fcis-2135	24	3	)	)	PUNCT
fcis-2135	24	4	as	as	ADP
fcis-2135	24	5	a	a	DET
fcis-2135	24	6	more	more	ADV
fcis-2135	24	7	flexible	flexible	ADJ
fcis-2135	24	8	participant	participant	NOUN
fcis-2135	24	9	in	in	ADP
fcis-2135	24	10	the	the	DET
fcis-2135	24	11	traffic	traffic	NOUN
fcis-2135	24	12	scene	scene	NOUN
fcis-2135	24	13	,	,	PUNCT
fcis-2135	24	14	it	it	PRON
fcis-2135	24	15	is	be	AUX
fcis-2135	24	16	a	a	DET
fcis-2135	24	17	difficult	difficult	ADJ
fcis-2135	24	18	task	task	NOUN
fcis-2135	24	19	to	to	PART
fcis-2135	24	20	accurately	accurately	ADV
fcis-2135	24	21	predict	predict	VERB
fcis-2135	24	22	the	the	DET
fcis-2135	24	23	future	future	ADJ
fcis-2135	24	24	trajectory	trajectory	NOUN
fcis-2135	24	25	of	of	ADP
fcis-2135	24	26	pedestrians	pedestrian	NOUN
fcis-2135	24	27	.	.	PUNCT
fcis-2135	25	1	however	however	ADV
fcis-2135	25	2	,	,	PUNCT
fcis-2135	25	3	by	by	ADP
fcis-2135	25	4	observing	observe	VERB
fcis-2135	25	5	the	the	DET
fcis-2135	25	6	trajectory	trajectory	NOUN
fcis-2135	25	7	of	of	ADP
fcis-2135	25	8	its	its	PRON
fcis-2135	25	9	historical	historical	ADJ
fcis-2135	25	10	moments	moment	NOUN
fcis-2135	25	11	,	,	PUNCT
fcis-2135	25	12	some	some	DET
fcis-2135	25	13	advanced	advanced	ADJ
fcis-2135	25	14	algorithms	algorithm	NOUN
fcis-2135	25	15	can	can	AUX
fcis-2135	25	16	be	be	AUX
fcis-2135	25	17	used	use	VERB
fcis-2135	25	18	to	to	PART
fcis-2135	25	19	roughly	roughly	ADV
fcis-2135	25	20	predict	predict	VERB
fcis-2135	25	21	the	the	DET
fcis-2135	25	22	future	future	ADJ
fcis-2135	25	23	trajectory	trajectory	NOUN
fcis-2135	25	24	of	of	ADP
fcis-2135	25	25	pedestrians	pedestrian	NOUN
fcis-2135	25	26	.	.	PUNCT
fcis-2135	26	1	however	however	ADV
fcis-2135	26	2	,	,	PUNCT
fcis-2135	26	3	in	in	ADP
fcis-2135	26	4	actual	actual	ADJ
fcis-2135	26	5	traffic	traffic	NOUN
fcis-2135	26	6	scenarios	scenario	NOUN
fcis-2135	26	7	,	,	PUNCT
fcis-2135	26	8	compared	compare	VERB
fcis-2135	26	9	with	with	ADP
fcis-2135	26	10	traffic	traffic	NOUN
fcis-2135	26	11	participants	participant	NOUN
fcis-2135	26	12	such	such	ADJ
fcis-2135	26	13	as	as	ADP
fcis-2135	26	14	vehicles	vehicle	NOUN
fcis-2135	26	15	,	,	PUNCT
fcis-2135	26	16	pedestrian	pedestrian	NOUN
fcis-2135	26	17	movement	movement	NOUN
fcis-2135	26	18	is	be	AUX
fcis-2135	26	19	more	more	ADV
fcis-2135	26	20	flexible	flexible	ADJ
fcis-2135	26	21	and	and	CCONJ
fcis-2135	26	22	can	can	AUX
fcis-2135	26	23	turn	turn	VERB
fcis-2135	26	24	,	,	PUNCT
fcis-2135	26	25	stop	stop	VERB
fcis-2135	26	26	and	and	CCONJ
fcis-2135	26	27	move	move	VERB
fcis-2135	26	28	at	at	ADP
fcis-2135	26	29	any	any	DET
fcis-2135	26	30	time	time	NOUN
fcis-2135	26	31	.	.	PUNCT
fcis-2135	27	1	it	it	PRON
fcis-2135	27	2	is	be	AUX
fcis-2135	27	3	difficult	difficult	ADJ
fcis-2135	27	4	to	to	PART
fcis-2135	27	5	establish	establish	VERB
fcis-2135	27	6	a	a	DET
fcis-2135	27	7	kinematic	kinematic	ADJ
fcis-2135	27	8	model	model	NOUN
fcis-2135	27	9	suitable	suitable	ADJ
fcis-2135	27	10	for	for	ADP
fcis-2135	27	11	pedestrians	pedestrian	NOUN
fcis-2135	27	12	,	,	PUNCT
fcis-2135	27	13	and	and	CCONJ
fcis-2135	27	14	sometimes	sometimes	ADV
fcis-2135	27	15	even	even	ADV
fcis-2135	27	16	drivers	driver	NOUN
fcis-2135	27	17	are	be	AUX
fcis-2135	27	18	difficult	difficult	ADJ
fcis-2135	27	19	to	to	PART
fcis-2135	27	20	predict	predict	VERB
fcis-2135	27	21	the	the	DET
fcis-2135	27	22	future	future	ADJ
fcis-2135	27	23	trajectory	trajectory	NOUN
fcis-2135	27	24	of	of	ADP
fcis-2135	27	25	pedestrians	pedestrian	NOUN
fcis-2135	27	26	.	.	PUNCT
fcis-2135	28	1	(	(	PUNCT
fcis-2135	28	2	2	2	X
fcis-2135	28	3	)	)	PUNCT
fcis-2135	28	4	in	in	ADP
fcis-2135	28	5	the	the	DET
fcis-2135	28	6	actual	actual	ADJ
fcis-2135	28	7	traffic	traffic	NOUN
fcis-2135	28	8	scene	scene	NOUN
fcis-2135	28	9	,	,	PUNCT
fcis-2135	28	10	the	the	DET
fcis-2135	28	11	future	future	ADJ
fcis-2135	28	12	movement	movement	NOUN
fcis-2135	28	13	of	of	ADP
fcis-2135	28	14	a	a	DET
fcis-2135	28	15	pedestrian	pedestrian	NOUN
fcis-2135	28	16	is	be	AUX
fcis-2135	28	17	not	not	PART
fcis-2135	28	18	only	only	ADV
fcis-2135	28	19	dominated	dominate	VERB
fcis-2135	28	20	by	by	ADP
fcis-2135	28	21	personal	personal	ADJ
fcis-2135	28	22	will	will	NOUN
fcis-2135	28	23	,	,	PUNCT
fcis-2135	28	24	but	but	CCONJ
fcis-2135	28	25	also	also	ADV
fcis-2135	28	26	by	by	ADP
fcis-2135	28	27	the	the	DET
fcis-2135	28	28	surrounding	surround	VERB
fcis-2135	28	29	traffic	traffic	NOUN
fcis-2135	28	30	environment	environment	NOUN
fcis-2135	28	31	and	and	CCONJ
fcis-2135	28	32	the	the	DET
fcis-2135	28	33	influence	influence	NOUN
fcis-2135	28	34	of	of	ADP
fcis-2135	28	35	the	the	DET
fcis-2135	28	36	surrounding	surround	VERB
fcis-2135	28	37	pedestrians	pedestrian	NOUN
fcis-2135	28	38	(	(	PUNCT
fcis-2135	28	39	such	such	ADJ
fcis-2135	28	40	as	as	ADP
fcis-2135	28	41	walking	walk	VERB
fcis-2135	28	42	together	together	ADV
fcis-2135	28	43	,	,	PUNCT
fcis-2135	28	44	interaction	interaction	NOUN
fcis-2135	28	45	,	,	PUNCT
fcis-2135	28	46	etc	etc	X
fcis-2135	28	47	.	.	X
fcis-2135	28	48	)	)	PUNCT
fcis-2135	28	49	.	.	PUNCT
fcis-2135	29	1	according	accord	VERB
fcis-2135	29	2	to	to	ADP
fcis-2135	29	3	the	the	DET
fcis-2135	29	4	research	research	NOUN
fcis-2135	29	5	of	of	ADP
fcis-2135	29	6	moussaid	moussaid	PROPN
fcis-2135	29	7	m	m	PROPN
fcis-2135	29	8	et	et	NOUN
fcis-2135	29	9	al	al	PROPN
fcis-2135	29	10	.	.	PUNCT
fcis-2135	30	1	[	[	X
fcis-2135	30	2	2	2	NUM
fcis-2135	30	3	]	]	PUNCT
fcis-2135	30	4	,	,	PUNCT
fcis-2135	30	5	70	70	NUM
fcis-2135	30	6	%	%	NOUN
fcis-2135	30	7	of	of	ADP
fcis-2135	30	8	pedestrians	pedestrian	NOUN
fcis-2135	30	9	tend	tend	VERB
fcis-2135	30	10	to	to	PART
fcis-2135	30	11	walk	walk	VERB
fcis-2135	30	12	together	together	ADV
fcis-2135	30	13	,	,	PUNCT
fcis-2135	30	14	and	and	CCONJ
fcis-2135	30	15	the	the	DET
fcis-2135	30	16	accompanying	accompany	VERB
fcis-2135	30	17	pedestrians	pedestrian	NOUN
fcis-2135	30	18	often	often	ADV
fcis-2135	30	19	interact	interact	VERB
fcis-2135	30	20	in	in	ADP
fcis-2135	30	21	the	the	DET
fcis-2135	30	22	same	same	ADJ
fcis-2135	30	23	time	time	NOUN
fcis-2135	30	24	and	and	CCONJ
fcis-2135	30	25	space	space	NOUN
fcis-2135	30	26	.	.	PUNCT
fcis-2135	31	1	this	this	DET
fcis-2135	31	2	interaction	interaction	NOUN
fcis-2135	31	3	between	between	ADP
fcis-2135	31	4	pedestrians	pedestrian	NOUN
fcis-2135	31	5	is	be	AUX
fcis-2135	31	6	very	very	ADV
fcis-2135	31	7	abstract	abstract	ADJ
fcis-2135	31	8	and	and	CCONJ
fcis-2135	31	9	difficult	difficult	ADJ
fcis-2135	31	10	to	to	PART
fcis-2135	31	11	model	model	VERB
fcis-2135	31	12	accurately	accurately	ADV
fcis-2135	31	13	in	in	ADP
fcis-2135	31	14	the	the	DET
fcis-2135	31	15	algorithm	algorithm	NOUN
fcis-2135	31	16	.	.	PUNCT
fcis-2135	32	1	(	(	PUNCT
fcis-2135	32	2	3	3	X
fcis-2135	32	3	)	)	PUNCT
fcis-2135	32	4	the	the	DET
fcis-2135	32	5	realization	realization	NOUN
fcis-2135	32	6	of	of	ADP
fcis-2135	32	7	the	the	DET
fcis-2135	32	8	conventional	conventional	ADJ
fcis-2135	32	9	pedestrian	pedestrian	NOUN
fcis-2135	32	10	trajectory	trajectory	NOUN
fcis-2135	32	11	prediction	prediction	NOUN
fcis-2135	32	12	algorithm	algorithm	NOUN
fcis-2135	32	13	model	model	NOUN
fcis-2135	32	14	is	be	AUX
fcis-2135	32	15	to	to	PART
fcis-2135	32	16	find	find	VERB
fcis-2135	32	17	a	a	DET
fcis-2135	32	18	function	function	NOUN
fcis-2135	32	19	mapping	mapping	NOUN
fcis-2135	32	20	from	from	ADP
fcis-2135	32	21	input	input	NOUN
fcis-2135	32	22	to	to	ADP
fcis-2135	32	23	output	output	NOUN
fcis-2135	32	24	.	.	PUNCT
fcis-2135	33	1	for	for	ADP
fcis-2135	33	2	the	the	DET
fcis-2135	33	3	trajectory	trajectory	NOUN
fcis-2135	33	4	prediction	prediction	NOUN
fcis-2135	33	5	model	model	NOUN
fcis-2135	33	6	,	,	PUNCT
fcis-2135	33	7	it	it	PRON
fcis-2135	33	8	corresponds	correspond	VERB
fcis-2135	33	9	to	to	ADP
fcis-2135	33	10	the	the	DET
fcis-2135	33	11	mapping	mapping	NOUN
fcis-2135	33	12	between	between	ADP
fcis-2135	33	13	different	different	ADJ
fcis-2135	33	14	sequences	sequence	NOUN
fcis-2135	33	15	.	.	PUNCT
fcis-2135	34	1	the	the	DET
fcis-2135	34	2	conventional	conventional	ADJ
fcis-2135	34	3	model	model	NOUN
fcis-2135	34	4	or	or	CCONJ
fcis-2135	34	5	training	training	NOUN
fcis-2135	34	6	method	method	NOUN
fcis-2135	34	7	is	be	AUX
fcis-2135	34	8	easy	easy	ADJ
fcis-2135	34	9	to	to	PART
fcis-2135	34	10	make	make	VERB
fcis-2135	34	11	the	the	DET
fcis-2135	34	12	model	model	NOUN
fcis-2135	34	13	prediction	prediction	NOUN
fcis-2135	34	14	result	result	NOUN
fcis-2135	34	15	fall	fall	VERB
fcis-2135	34	16	into	into	ADP
fcis-2135	34	17	a	a	DET
fcis-2135	34	18	compromise	compromise	NOUN
fcis-2135	34	19	state	state	NOUN
fcis-2135	34	20	(	(	PUNCT
fcis-2135	34	21	the	the	DET
fcis-2135	34	22	prediction	prediction	NOUN
fcis-2135	34	23	result	result	NOUN
fcis-2135	34	24	tends	tend	VERB
fcis-2135	34	25	to	to	PART
fcis-2135	34	26	predict	predict	VERB
fcis-2135	34	27	a	a	DET
fcis-2135	34	28	compromise	compromise	NOUN
fcis-2135	34	29	trajectory	trajectory	NOUN
fcis-2135	34	30	)	)	PUNCT
fcis-2135	34	31	.	.	PUNCT
fcis-2135	35	1	obviously	obviously	ADV
fcis-2135	35	2	,	,	PUNCT
fcis-2135	35	3	the	the	DET
fcis-2135	35	4	conventional	conventional	ADJ
fcis-2135	35	5	training	training	NOUN
fcis-2135	35	6	model	model	NOUN
fcis-2135	35	7	can	can	AUX
fcis-2135	35	8	not	not	PART
fcis-2135	35	9	effectively	effectively	ADV
fcis-2135	35	10	and	and	CCONJ
fcis-2135	35	11	accurately	accurately	ADV
fcis-2135	35	12	predict	predict	VERB
fcis-2135	35	13	the	the	DET
fcis-2135	35	14	pedestrian	pedestrian	NOUN
fcis-2135	35	15	trajectory	trajectory	NOUN
fcis-2135	35	16	.	.	PUNCT
fcis-2135	36	1	due	due	ADP
fcis-2135	36	2	to	to	ADP
fcis-2135	36	3	the	the	DET
fcis-2135	36	4	influence	influence	NOUN
fcis-2135	36	5	of	of	ADP
fcis-2135	36	6	pedestrian	pedestrian	NOUN
fcis-2135	36	7	's	's	PART
fcis-2135	36	8	subjective	subjective	ADJ
fcis-2135	36	9	intention	intention	NOUN
fcis-2135	36	10	and	and	CCONJ
fcis-2135	36	11	objective	objective	ADJ
fcis-2135	36	12	environment	environment	NOUN
fcis-2135	36	13	,	,	PUNCT
fcis-2135	36	14	the	the	DET
fcis-2135	36	15	interaction	interaction	NOUN
fcis-2135	36	16	between	between	ADP
fcis-2135	36	17	pedestrians	pedestrian	NOUN
fcis-2135	36	18	and	and	CCONJ
fcis-2135	36	19	between	between	ADP
fcis-2135	36	20	pedestrians	pedestrian	NOUN
fcis-2135	36	21	and	and	CCONJ
fcis-2135	36	22	the	the	DET
fcis-2135	36	23	environment	environment	NOUN
fcis-2135	36	24	becomes	become	VERB
fcis-2135	36	25	complex	complex	ADJ
fcis-2135	36	26	and	and	CCONJ
fcis-2135	36	27	abstract	abstract	ADJ
fcis-2135	36	28	.	.	PUNCT
fcis-2135	37	1	the	the	DET
fcis-2135	37	2	traditional	traditional	ADJ
fcis-2135	37	3	pedestrian	pedestrian	NOUN
fcis-2135	37	4	trajectory	trajectory	NOUN
fcis-2135	37	5	prediction	prediction	NOUN
fcis-2135	37	6	model	model	NOUN
fcis-2135	37	7	has	have	AUX
fcis-2135	37	8	been	be	AUX
fcis-2135	37	9	unable	unable	ADJ
fcis-2135	37	10	to	to	PART
fcis-2135	37	11	meet	meet	VERB
fcis-2135	37	12	the	the	DET
fcis-2135	37	13	interaction	interaction	NOUN
fcis-2135	37	14	in	in	ADP
fcis-2135	37	15	responsible	responsible	ADJ
fcis-2135	37	16	scenarios	scenario	NOUN
fcis-2135	37	17	,	,	PUNCT
fcis-2135	37	18	and	and	CCONJ
fcis-2135	37	19	the	the	DET
fcis-2135	37	20	environmental	environmental	ADJ
fcis-2135	37	21	adaptability	adaptability	NOUN
fcis-2135	37	22	is	be	AUX
fcis-2135	37	23	poor	poor	ADJ
fcis-2135	37	24	,	,	PUNCT
fcis-2135	37	25	which	which	PRON
fcis-2135	37	26	limits	limit	VERB
fcis-2135	37	27	the	the	DET
fcis-2135	37	28	prediction	prediction	NOUN
fcis-2135	37	29	performance	performance	NOUN
fcis-2135	37	30	of	of	ADP
fcis-2135	37	31	the	the	DET
fcis-2135	37	32	model	model	NOUN
fcis-2135	37	33	.	.	PUNCT
fcis-2135	38	1	with	with	ADP
fcis-2135	38	2	the	the	DET
fcis-2135	38	3	development	development	NOUN
fcis-2135	38	4	of	of	ADP
fcis-2135	38	5	deep	deep	ADJ
fcis-2135	38	6	learning	learning	NOUN
fcis-2135	38	7	,	,	PUNCT
fcis-2135	38	8	neural	neural	ADJ
fcis-2135	38	9	networks	network	NOUN
fcis-2135	38	10	have	have	AUX
fcis-2135	38	11	made	make	VERB
fcis-2135	38	12	major	major	ADJ
fcis-2135	38	13	breakthroughs	breakthrough	NOUN
fcis-2135	38	14	in	in	ADP
fcis-2135	38	15	the	the	DET
fcis-2135	38	16	fields	field	NOUN
fcis-2135	38	17	of	of	ADP
fcis-2135	38	18	image	image	NOUN
fcis-2135	38	19	recognition	recognition	NOUN
fcis-2135	38	20	,	,	PUNCT
fcis-2135	38	21	classification	classification	NOUN
fcis-2135	38	22	,	,	PUNCT
fcis-2135	38	23	and	and	CCONJ
fcis-2135	38	24	tracking	tracking	NOUN
fcis-2135	38	25	.	.	PUNCT
fcis-2135	39	1	its	its	PRON
fcis-2135	39	2	complete	complete	ADJ
fcis-2135	39	3	theoretical	theoretical	ADJ
fcis-2135	39	4	system	system	NOUN
fcis-2135	39	5	and	and	CCONJ
fcis-2135	39	6	rich	rich	ADJ
fcis-2135	39	7	network	network	NOUN
fcis-2135	39	8	models	model	NOUN
fcis-2135	39	9	provide	provide	VERB
fcis-2135	39	10	the	the	DET
fcis-2135	39	11	necessary	necessary	ADJ
fcis-2135	39	12	conditions	condition	NOUN
fcis-2135	39	13	for	for	ADP
fcis-2135	39	14	deep	deep	ADJ
fcis-2135	39	15	learning	learning	NOUN
fcis-2135	39	16	to	to	PART
fcis-2135	39	17	be	be	AUX
fcis-2135	39	18	applied	apply	VERB
fcis-2135	39	19	to	to	ADP
fcis-2135	39	20	the	the	DET
fcis-2135	39	21	field	field	NOUN
fcis-2135	39	22	of	of	ADP
fcis-2135	39	23	pedestrian	pedestrian	NOUN
fcis-2135	39	24	trajectories	trajectory	NOUN
fcis-2135	39	25	.	.	PUNCT
fcis-2135	40	1	in	in	ADP
fcis-2135	40	2	particular	particular	ADJ
fcis-2135	40	3	,	,	PUNCT
fcis-2135	40	4	recurrent	recurrent	ADJ
fcis-2135	40	5	neural	neural	ADJ
fcis-2135	40	6	network	network	NOUN
fcis-2135	40	7	(	(	PUNCT
fcis-2135	40	8	rnn	rnn	PROPN
fcis-2135	40	9	)	)	PUNCT
fcis-2135	40	10	,	,	PUNCT
fcis-2135	40	11	generative	generative	ADJ
fcis-2135	40	12	adversarial	adversarial	ADJ
fcis-2135	40	13	network	network	NOUN
fcis-2135	40	14	(	(	PUNCT
fcis-2135	40	15	gan	gan	PROPN
fcis-2135	40	16	)	)	PUNCT
fcis-2135	40	17	and	and	CCONJ
fcis-2135	40	18	graph	graph	VERB
fcis-2135	40	19	convolutional	convolutional	ADJ
fcis-2135	40	20	network	network	NOUN
fcis-2135	40	21	(	(	PUNCT
fcis-2135	40	22	gcn	gcn	NOUN
fcis-2135	40	23	)	)	PUNCT
fcis-2135	40	24	for	for	ADP
fcis-2135	40	25	sequence	sequence	NOUN
fcis-2135	40	26	learning	learn	VERB
fcis-2135	40	27	have	have	AUX
fcis-2135	40	28	become	become	VERB
fcis-2135	40	29	the	the	DET
fcis-2135	40	30	main	main	ADJ
fcis-2135	40	31	networks	network	NOUN
fcis-2135	40	32	for	for	ADP
fcis-2135	40	33	pedestrian	pedestrian	NOUN
fcis-2135	40	34	trajectory	trajectory	NOUN
fcis-2135	40	35	69	69	NUM
fcis-2135	40	36	prediction	prediction	NOUN
fcis-2135	40	37	modeling	modeling	NOUN
fcis-2135	40	38	.	.	PUNCT
fcis-2135	41	1	the	the	DET
fcis-2135	41	2	high	high	ADJ
fcis-2135	41	3	dynamics	dynamic	NOUN
fcis-2135	41	4	and	and	CCONJ
fcis-2135	41	5	randomness	randomness	NOUN
fcis-2135	41	6	of	of	ADP
fcis-2135	41	7	pedestrian	pedestrian	NOUN
fcis-2135	41	8	trajectories	trajectory	NOUN
fcis-2135	41	9	and	and	CCONJ
fcis-2135	41	10	the	the	DET
fcis-2135	41	11	complex	complex	ADJ
fcis-2135	41	12	interaction	interaction	NOUN
fcis-2135	41	13	with	with	ADP
fcis-2135	41	14	traffic	traffic	NOUN
fcis-2135	41	15	environment	environment	NOUN
fcis-2135	41	16	agents	agent	NOUN
fcis-2135	41	17	make	make	VERB
fcis-2135	41	18	trajectory	trajectory	NOUN
fcis-2135	41	19	prediction	prediction	NOUN
fcis-2135	41	20	challenging	challenging	ADJ
fcis-2135	41	21	.	.	PUNCT
fcis-2135	42	1	however	however	ADV
fcis-2135	42	2	,	,	PUNCT
fcis-2135	42	3	it	it	PRON
fcis-2135	42	4	is	be	AUX
fcis-2135	42	5	still	still	ADV
fcis-2135	42	6	necessary	necessary	ADJ
fcis-2135	42	7	to	to	PART
fcis-2135	42	8	predict	predict	VERB
fcis-2135	42	9	pedestrian	pedestrian	NOUN
fcis-2135	42	10	trajectories	trajectory	NOUN
fcis-2135	42	11	for	for	ADP
fcis-2135	42	12	a	a	DET
fcis-2135	42	13	long	long	ADJ
fcis-2135	42	14	time	time	NOUN
fcis-2135	42	15	,	,	PUNCT
fcis-2135	42	16	which	which	PRON
fcis-2135	42	17	has	have	VERB
fcis-2135	42	18	a	a	DET
fcis-2135	42	19	great	great	ADJ
fcis-2135	42	20	impact	impact	NOUN
fcis-2135	42	21	on	on	ADP
fcis-2135	42	22	the	the	DET
fcis-2135	42	23	active	active	ADJ
fcis-2135	42	24	planning	planning	NOUN
fcis-2135	42	25	and	and	CCONJ
fcis-2135	42	26	decision	decision	NOUN
fcis-2135	42	27	-	-	PUNCT
fcis-2135	42	28	making	making	NOUN
fcis-2135	42	29	of	of	ADP
fcis-2135	42	30	autonomous	autonomous	ADJ
fcis-2135	42	31	vehicles	vehicle	NOUN
fcis-2135	42	32	.	.	PUNCT
fcis-2135	43	1	at	at	ADP
fcis-2135	43	2	present	present	ADJ
fcis-2135	43	3	,	,	PUNCT
fcis-2135	43	4	the	the	DET
fcis-2135	43	5	research	research	NOUN
fcis-2135	43	6	on	on	ADP
fcis-2135	43	7	pedestrian	pedestrian	NOUN
fcis-2135	43	8	trajectory	trajectory	NOUN
fcis-2135	43	9	prediction	prediction	NOUN
fcis-2135	43	10	is	be	AUX
fcis-2135	43	11	increasing	increase	VERB
fcis-2135	43	12	at	at	ADP
fcis-2135	43	13	home	home	NOUN
fcis-2135	43	14	and	and	CCONJ
fcis-2135	43	15	abroad	abroad	ADV
fcis-2135	43	16	,	,	PUNCT
fcis-2135	43	17	and	and	CCONJ
fcis-2135	43	18	it	it	PRON
fcis-2135	43	19	is	be	AUX
fcis-2135	43	20	necessary	necessary	ADJ
fcis-2135	43	21	to	to	PART
fcis-2135	43	22	review	review	VERB
fcis-2135	43	23	the	the	DET
fcis-2135	43	24	related	relate	VERB
fcis-2135	43	25	technologies	technology	NOUN
fcis-2135	43	26	and	and	CCONJ
fcis-2135	43	27	literatures	literature	NOUN
fcis-2135	43	28	in	in	ADP
fcis-2135	43	29	this	this	DET
fcis-2135	43	30	field	field	NOUN
fcis-2135	43	31	.	.	PUNCT
fcis-2135	44	1	in	in	ADP
fcis-2135	44	2	this	this	DET
fcis-2135	44	3	paper	paper	NOUN
fcis-2135	44	4	,	,	PUNCT
fcis-2135	44	5	the	the	DET
fcis-2135	44	6	problem	problem	NOUN
fcis-2135	44	7	description	description	NOUN
fcis-2135	44	8	,	,	PUNCT
fcis-2135	44	9	research	research	NOUN
fcis-2135	44	10	development	development	NOUN
fcis-2135	44	11	and	and	CCONJ
fcis-2135	44	12	problem	problem	NOUN
fcis-2135	44	13	processing	processing	NOUN
fcis-2135	44	14	flow	flow	NOUN
fcis-2135	44	15	of	of	ADP
fcis-2135	44	16	pedestrian	pedestrian	NOUN
fcis-2135	44	17	trajectory	trajectory	NOUN
fcis-2135	44	18	prediction	prediction	NOUN
fcis-2135	44	19	are	be	AUX
fcis-2135	44	20	sorted	sort	VERB
fcis-2135	44	21	out	out	ADV
fcis-2135	44	22	,	,	PUNCT
fcis-2135	44	23	and	and	CCONJ
fcis-2135	44	24	the	the	DET
fcis-2135	44	25	research	research	NOUN
fcis-2135	44	26	progress	progress	NOUN
fcis-2135	44	27	of	of	ADP
fcis-2135	44	28	pedestrian	pedestrian	NOUN
fcis-2135	44	29	trajectory	trajectory	NOUN
fcis-2135	44	30	prediction	prediction	NOUN
fcis-2135	44	31	,	,	PUNCT
fcis-2135	44	32	especially	especially	ADV
fcis-2135	44	33	the	the	DET
fcis-2135	44	34	research	research	NOUN
fcis-2135	44	35	results	result	NOUN
fcis-2135	44	36	in	in	ADP
fcis-2135	44	37	recent	recent	ADJ
fcis-2135	44	38	years	year	NOUN
fcis-2135	44	39	,	,	PUNCT
fcis-2135	44	40	is	be	AUX
fcis-2135	44	41	reviewed	review	VERB
fcis-2135	44	42	.	.	PUNCT
fcis-2135	45	1	the	the	DET
fcis-2135	45	2	main	main	ADJ
fcis-2135	45	3	contents	content	NOUN
fcis-2135	45	4	of	of	ADP
fcis-2135	45	5	the	the	DET
fcis-2135	45	6	article	article	NOUN
fcis-2135	45	7	are	be	AUX
fcis-2135	45	8	as	as	SCONJ
fcis-2135	45	9	follows	follow	VERB
fcis-2135	45	10	:	:	PUNCT
fcis-2135	45	11	part	part	NOUN
fcis-2135	45	12	1	1	NUM
fcis-2135	45	13	introduces	introduce	VERB
fcis-2135	45	14	the	the	DET
fcis-2135	45	15	current	current	ADJ
fcis-2135	45	16	pedestrian	pedestrian	NOUN
fcis-2135	45	17	trajectory	trajectory	NOUN
fcis-2135	45	18	prediction	prediction	NOUN
fcis-2135	45	19	problem	problem	NOUN
fcis-2135	45	20	and	and	CCONJ
fcis-2135	45	21	leads	lead	VERB
fcis-2135	45	22	to	to	ADP
fcis-2135	45	23	the	the	DET
fcis-2135	45	24	common	common	ADJ
fcis-2135	45	25	pedestrian	pedestrian	NOUN
fcis-2135	45	26	trajectory	trajectory	NOUN
fcis-2135	45	27	prediction	prediction	NOUN
fcis-2135	45	28	methods	method	NOUN
fcis-2135	45	29	;	;	PUNCT
fcis-2135	45	30	in	in	ADP
fcis-2135	45	31	the	the	DET
fcis-2135	45	32	second	second	ADJ
fcis-2135	45	33	part	part	NOUN
fcis-2135	45	34	,	,	PUNCT
fcis-2135	45	35	the	the	DET
fcis-2135	45	36	existing	exist	VERB
fcis-2135	45	37	trajectory	trajectory	NOUN
fcis-2135	45	38	prediction	prediction	NOUN
fcis-2135	45	39	methods	method	NOUN
fcis-2135	45	40	are	be	AUX
fcis-2135	45	41	classified	classify	VERB
fcis-2135	45	42	,	,	PUNCT
fcis-2135	45	43	and	and	CCONJ
fcis-2135	45	44	the	the	DET
fcis-2135	45	45	methods	method	NOUN
fcis-2135	45	46	based	base	VERB
fcis-2135	45	47	on	on	ADP
fcis-2135	45	48	shallow	shallow	ADJ
fcis-2135	45	49	learning	learning	NOUN
fcis-2135	45	50	and	and	CCONJ
fcis-2135	45	51	machine	machine	NOUN
fcis-2135	45	52	learning	learning	NOUN
fcis-2135	45	53	are	be	AUX
fcis-2135	45	54	briefly	briefly	ADV
fcis-2135	45	55	summarized	summarize	VERB
fcis-2135	45	56	.	.	PUNCT
fcis-2135	46	1	the	the	DET
fcis-2135	46	2	advantages	advantage	NOUN
fcis-2135	46	3	and	and	CCONJ
fcis-2135	46	4	disadvantages	disadvantage	NOUN
fcis-2135	46	5	of	of	ADP
fcis-2135	46	6	pedestrian	pedestrian	NOUN
fcis-2135	46	7	trajectory	trajectory	NOUN
fcis-2135	46	8	prediction	prediction	NOUN
fcis-2135	46	9	methods	method	NOUN
fcis-2135	46	10	based	base	VERB
fcis-2135	46	11	on	on	ADP
fcis-2135	46	12	different	different	ADJ
fcis-2135	46	13	neural	neural	ADJ
fcis-2135	46	14	networks	network	NOUN
fcis-2135	46	15	are	be	AUX
fcis-2135	46	16	compared	compare	VERB
fcis-2135	46	17	.	.	PUNCT
fcis-2135	47	1	the	the	DET
fcis-2135	47	2	third	third	ADJ
fcis-2135	47	3	part	part	NOUN
fcis-2135	47	4	introduces	introduce	VERB
fcis-2135	47	5	the	the	DET
fcis-2135	47	6	current	current	ADJ
fcis-2135	47	7	mainstream	mainstream	NOUN
fcis-2135	47	8	trajectory	trajectory	NOUN
fcis-2135	47	9	prediction	prediction	NOUN
fcis-2135	47	10	public	public	ADJ
fcis-2135	47	11	data	datum	NOUN
fcis-2135	47	12	set	set	VERB
fcis-2135	47	13	in	in	ADP
fcis-2135	47	14	the	the	DET
fcis-2135	47	15	industry	industry	NOUN
fcis-2135	47	16	.	.	PUNCT
fcis-2135	48	1	after	after	ADP
fcis-2135	48	2	testing	test	VERB
fcis-2135	48	3	some	some	DET
fcis-2135	48	4	trajectory	trajectory	NOUN
fcis-2135	48	5	prediction	prediction	NOUN
fcis-2135	48	6	methods	method	NOUN
fcis-2135	48	7	in	in	ADP
fcis-2135	48	8	the	the	DET
fcis-2135	48	9	data	data	NOUN
fcis-2135	48	10	set	set	VERB
fcis-2135	48	11	,	,	PUNCT
fcis-2135	48	12	the	the	DET
fcis-2135	48	13	methods	method	NOUN
fcis-2135	48	14	to	to	PART
fcis-2135	48	15	obtain	obtain	VERB
fcis-2135	48	16	excellent	excellent	ADJ
fcis-2135	48	17	test	test	NOUN
fcis-2135	48	18	results	result	NOUN
fcis-2135	48	19	are	be	AUX
fcis-2135	48	20	analyzed	analyze	VERB
fcis-2135	48	21	and	and	CCONJ
fcis-2135	48	22	compared	compare	VERB
fcis-2135	48	23	.	.	PUNCT
fcis-2135	49	1	part	part	NOUN
fcis-2135	49	2	4	4	NUM
fcis-2135	49	3	and	and	CCONJ
fcis-2135	49	4	5	5	NUM
fcis-2135	49	5	summarize	summarize	VERB
fcis-2135	49	6	the	the	DET
fcis-2135	49	7	existing	exist	VERB
fcis-2135	49	8	problems	problem	NOUN
fcis-2135	49	9	and	and	CCONJ
fcis-2135	49	10	future	future	ADJ
fcis-2135	49	11	research	research	NOUN
fcis-2135	49	12	directions	direction	NOUN
fcis-2135	49	13	of	of	ADP
fcis-2135	49	14	pedestrian	pedestrian	NOUN
fcis-2135	49	15	trajectory	trajectory	NOUN
fcis-2135	49	16	prediction	prediction	NOUN
fcis-2135	49	17	.	.	PUNCT
fcis-2135	50	1	the	the	DET
fcis-2135	50	2	last	last	ADJ
fcis-2135	50	3	part	part	NOUN
fcis-2135	50	4	summarizes	summarize	VERB
fcis-2135	50	5	the	the	DET
fcis-2135	50	6	full	full	ADJ
fcis-2135	50	7	text	text	NOUN
fcis-2135	50	8	.	.	PUNCT
fcis-2135	51	1	2	2	X
fcis-2135	51	2	.	.	X
fcis-2135	51	3	related	relate	VERB
fcis-2135	51	4	work	work	NOUN
fcis-2135	51	5	2.1	2.1	NUM
fcis-2135	51	6	.	.	PUNCT
fcis-2135	52	1	pedestrian	pedestrian	NOUN
fcis-2135	52	2	trajectory	trajectory	NOUN
fcis-2135	52	3	prediction	prediction	NOUN
fcis-2135	52	4	problem	problem	NOUN
fcis-2135	52	5	description	description	NOUN
fcis-2135	52	6	the	the	DET
fcis-2135	52	7	essence	essence	NOUN
fcis-2135	52	8	of	of	ADP
fcis-2135	52	9	the	the	DET
fcis-2135	52	10	pedestrian	pedestrian	NOUN
fcis-2135	52	11	trajectory	trajectory	NOUN
fcis-2135	52	12	prediction	prediction	NOUN
fcis-2135	52	13	problem	problem	NOUN
fcis-2135	52	14	is	be	AUX
fcis-2135	52	15	to	to	PART
fcis-2135	52	16	infer	infer	VERB
fcis-2135	52	17	the	the	DET
fcis-2135	52	18	location	location	NOUN
fcis-2135	52	19	and	and	CCONJ
fcis-2135	52	20	possible	possible	ADJ
fcis-2135	52	21	state	state	NOUN
fcis-2135	52	22	of	of	ADP
fcis-2135	52	23	the	the	DET
fcis-2135	52	24	pedestrian	pedestrian	NOUN
fcis-2135	52	25	in	in	ADP
fcis-2135	52	26	the	the	DET
fcis-2135	52	27	future	future	NOUN
fcis-2135	52	28	based	base	VERB
fcis-2135	52	29	on	on	ADP
fcis-2135	52	30	the	the	DET
fcis-2135	52	31	pedestrian	pedestrian	NOUN
fcis-2135	52	32	characteristic	characteristic	ADJ
fcis-2135	52	33	information	information	NOUN
fcis-2135	52	34	and	and	CCONJ
fcis-2135	52	35	the	the	DET
fcis-2135	52	36	environmental	environmental	ADJ
fcis-2135	52	37	information	information	NOUN
fcis-2135	52	38	.	.	PUNCT
fcis-2135	53	1	the	the	DET
fcis-2135	53	2	problem	problem	NOUN
fcis-2135	53	3	can	can	AUX
fcis-2135	53	4	be	be	AUX
fcis-2135	53	5	regarded	regard	VERB
fcis-2135	53	6	as	as	ADP
fcis-2135	53	7	a	a	DET
fcis-2135	53	8	sequential	sequential	ADJ
fcis-2135	53	9	decision	decision	NOUN
fcis-2135	53	10	problem	problem	NOUN
fcis-2135	53	11	,	,	PUNCT
fcis-2135	53	12	that	that	ADV
fcis-2135	53	13	is	is	ADV
fcis-2135	53	14	,	,	PUNCT
fcis-2135	53	15	through	through	ADP
fcis-2135	53	16	the	the	DET
fcis-2135	53	17	historical	historical	ADJ
fcis-2135	53	18	trajectory	trajectory	NOUN
fcis-2135	53	19	of	of	ADP
fcis-2135	53	20	the	the	DET
fcis-2135	53	21	pedestrian	pedestrian	NOUN
fcis-2135	53	22	observed	observe	VERB
fcis-2135	53	23	in	in	ADP
fcis-2135	53	24	the	the	DET
fcis-2135	53	25	past	past	NOUN
fcis-2135	53	26	,	,	PUNCT
fcis-2135	53	27	the	the	DET
fcis-2135	53	28	historical	historical	ADJ
fcis-2135	53	29	information	information	NOUN
fcis-2135	53	30	of	of	ADP
fcis-2135	53	31	the	the	DET
fcis-2135	53	32	self	self	NOUN
fcis-2135	53	33	-	-	PUNCT
fcis-2135	53	34	movement	movement	NOUN
fcis-2135	53	35	,	,	PUNCT
fcis-2135	53	36	etc	etc	X
fcis-2135	53	37	.	.	X
fcis-2135	53	38	,	,	PUNCT
fcis-2135	53	39	through	through	ADP
fcis-2135	53	40	the	the	DET
fcis-2135	53	41	establishment	establishment	NOUN
fcis-2135	53	42	of	of	ADP
fcis-2135	53	43	the	the	DET
fcis-2135	53	44	model	model	NOUN
fcis-2135	53	45	,	,	PUNCT
fcis-2135	53	46	the	the	DET
fcis-2135	53	47	machine	machine	NOUN
fcis-2135	53	48	learns	learn	VERB
fcis-2135	53	49	some	some	DET
fcis-2135	53	50	rules	rule	NOUN
fcis-2135	53	51	generated	generate	VERB
fcis-2135	53	52	by	by	ADP
fcis-2135	53	53	the	the	DET
fcis-2135	53	54	behavior	behavior	NOUN
fcis-2135	53	55	reasoning	reason	VERB
fcis-2135	53	56	,	,	PUNCT
fcis-2135	53	57	the	the	DET
fcis-2135	53	58	interaction	interaction	NOUN
fcis-2135	53	59	with	with	ADP
fcis-2135	53	60	others	other	NOUN
fcis-2135	53	61	,	,	PUNCT
fcis-2135	53	62	the	the	DET
fcis-2135	53	63	influence	influence	NOUN
fcis-2135	53	64	of	of	ADP
fcis-2135	53	65	the	the	DET
fcis-2135	53	66	surrounding	surround	VERB
fcis-2135	53	67	environment	environment	NOUN
fcis-2135	53	68	,	,	PUNCT
fcis-2135	53	69	etc.[3,4]to	etc.[3,4]to	PRON
fcis-2135	53	70	understand	understand	VERB
fcis-2135	53	71	the	the	DET
fcis-2135	53	72	human	human	ADJ
fcis-2135	53	73	movement	movement	NOUN
fcis-2135	53	74	in	in	ADP
fcis-2135	53	75	the	the	DET
fcis-2135	53	76	complex	complex	ADJ
fcis-2135	53	77	environment	environment	NOUN
fcis-2135	53	78	,	,	PUNCT
fcis-2135	53	79	so	so	SCONJ
fcis-2135	53	80	as	as	SCONJ
fcis-2135	53	81	to	to	PART
fcis-2135	53	82	predict	predict	VERB
fcis-2135	53	83	the	the	DET
fcis-2135	53	84	pedestrian	pedestrian	NOUN
fcis-2135	53	85	's	's	PART
fcis-2135	53	86	position	position	NOUN
fcis-2135	53	87	coordinates	coordinate	NOUN
fcis-2135	53	88	and	and	CCONJ
fcis-2135	53	89	motion	motion	NOUN
fcis-2135	53	90	trajectory	trajectory	NOUN
fcis-2135	53	91	in	in	ADP
fcis-2135	53	92	the	the	DET
fcis-2135	53	93	short	short	ADJ
fcis-2135	53	94	time	time	NOUN
fcis-2135	53	95	(	(	PUNCT
fcis-2135	53	96	such	such	ADJ
fcis-2135	53	97	as	as	ADP
fcis-2135	53	98	8s	8s	NUM
fcis-2135	53	99	)	)	PUNCT
fcis-2135	53	100	in	in	ADP
fcis-2135	53	101	the	the	DET
fcis-2135	53	102	future	future	NOUN
fcis-2135	53	103	according	accord	VERB
fcis-2135	53	104	to	to	ADP
fcis-2135	53	105	the	the	DET
fcis-2135	53	106	trajectory	trajectory	NOUN
fcis-2135	53	107	of	of	ADP
fcis-2135	53	108	the	the	DET
fcis-2135	53	109	pedestrian	pedestrian	NOUN
fcis-2135	53	110	in	in	ADP
fcis-2135	53	111	the	the	DET
fcis-2135	53	112	past	past	ADJ
fcis-2135	53	113	time	time	NOUN
fcis-2135	53	114	period	period	NOUN
fcis-2135	53	115	.	.	PUNCT
fcis-2135	54	1	due	due	ADP
fcis-2135	54	2	to	to	ADP
fcis-2135	54	3	the	the	DET
fcis-2135	54	4	complexity	complexity	NOUN
fcis-2135	54	5	and	and	CCONJ
fcis-2135	54	6	uncertainty	uncertainty	NOUN
fcis-2135	54	7	of	of	ADP
fcis-2135	54	8	pedestrianpedestrian	pedestrianpedestrian	NOUN
fcis-2135	54	9	and	and	CCONJ
fcis-2135	54	10	environment	environment	NOUN
fcis-2135	54	11	interaction	interaction	NOUN
fcis-2135	54	12	,	,	PUNCT
fcis-2135	54	13	pedestrian	pedestrian	NOUN
fcis-2135	54	14	trajectory	trajectory	NOUN
fcis-2135	54	15	prediction	prediction	NOUN
fcis-2135	54	16	is	be	AUX
fcis-2135	54	17	difficult	difficult	ADJ
fcis-2135	54	18	.	.	PUNCT
fcis-2135	55	1	traditional	traditional	ADJ
fcis-2135	55	2	methods	method	NOUN
fcis-2135	55	3	have	have	AUX
fcis-2135	55	4	conducted	conduct	VERB
fcis-2135	55	5	a	a	DET
fcis-2135	55	6	series	series	NOUN
fcis-2135	55	7	of	of	ADP
fcis-2135	55	8	studies	study	NOUN
fcis-2135	55	9	on	on	ADP
fcis-2135	55	10	pedestrian	pedestrian	NOUN
fcis-2135	55	11	interaction	interaction	NOUN
fcis-2135	55	12	through	through	ADP
fcis-2135	55	13	social	social	ADJ
fcis-2135	55	14	force	force	NOUN
fcis-2135	55	15	model	model	NOUN
fcis-2135	55	16	[	[	X
fcis-2135	55	17	5	5	NUM
fcis-2135	55	18	-	-	SYM
fcis-2135	55	19	8	8	NUM
fcis-2135	55	20	]	]	PUNCT
fcis-2135	55	21	,	,	PUNCT
fcis-2135	55	22	multi	multi	ADJ
fcis-2135	55	23	-	-	ADJ
fcis-2135	55	24	model	model	ADJ
fcis-2135	55	25	method	method	NOUN
fcis-2135	55	26	and	and	CCONJ
fcis-2135	55	27	mixed	mixed	ADJ
fcis-2135	55	28	estimation	estimation	NOUN
fcis-2135	55	29	[	[	X
fcis-2135	55	30	910	910	X
fcis-2135	55	31	]	]	PUNCT
fcis-2135	55	32	,	,	PUNCT
fcis-2135	55	33	but	but	CCONJ
fcis-2135	55	34	the	the	DET
fcis-2135	55	35	above	above	ADJ
fcis-2135	55	36	methods	method	NOUN
fcis-2135	55	37	have	have	VERB
fcis-2135	55	38	poor	poor	ADJ
fcis-2135	55	39	universality	universality	NOUN
fcis-2135	55	40	and	and	CCONJ
fcis-2135	55	41	have	have	VERB
fcis-2135	55	42	certain	certain	ADJ
fcis-2135	55	43	limitations	limitation	NOUN
fcis-2135	55	44	.	.	PUNCT
fcis-2135	56	1	in	in	ADP
fcis-2135	56	2	recent	recent	ADJ
fcis-2135	56	3	years	year	NOUN
fcis-2135	56	4	,	,	PUNCT
fcis-2135	56	5	with	with	ADP
fcis-2135	56	6	the	the	DET
fcis-2135	56	7	development	development	NOUN
fcis-2135	56	8	of	of	ADP
fcis-2135	56	9	deep	deep	ADJ
fcis-2135	56	10	learning	learning	NOUN
fcis-2135	56	11	,	,	PUNCT
fcis-2135	56	12	pattern	pattern	NOUN
fcis-2135	56	13	-	-	PUNCT
fcis-2135	56	14	based	base	VERB
fcis-2135	56	15	methods	method	NOUN
fcis-2135	56	16	can	can	AUX
fcis-2135	56	17	learn	learn	VERB
fcis-2135	56	18	to	to	PART
fcis-2135	56	19	fit	fit	VERB
fcis-2135	56	20	different	different	ADJ
fcis-2135	56	21	functions	function	NOUN
fcis-2135	56	22	(	(	PUNCT
fcis-2135	56	23	such	such	ADJ
fcis-2135	56	24	as	as	ADP
fcis-2135	56	25	neural	neural	ADJ
fcis-2135	56	26	networks	network	NOUN
fcis-2135	56	27	)	)	PUNCT
fcis-2135	56	28	from	from	ADP
fcis-2135	56	29	data	datum	NOUN
fcis-2135	56	30	to	to	PART
fcis-2135	56	31	learn	learn	VERB
fcis-2135	56	32	human	human	ADJ
fcis-2135	56	33	interaction	interaction	NOUN
fcis-2135	56	34	perception	perception	NOUN
fcis-2135	56	35	,	,	PUNCT
fcis-2135	56	36	greatly	greatly	ADV
fcis-2135	56	37	improving	improve	VERB
fcis-2135	56	38	the	the	DET
fcis-2135	56	39	flexibility	flexibility	NOUN
fcis-2135	56	40	and	and	CCONJ
fcis-2135	56	41	generalization	generalization	NOUN
fcis-2135	56	42	ability	ability	NOUN
fcis-2135	56	43	of	of	ADP
fcis-2135	56	44	the	the	DET
fcis-2135	56	45	model	model	NOUN
fcis-2135	56	46	.	.	PUNCT
fcis-2135	57	1	since	since	SCONJ
fcis-2135	57	2	the	the	DET
fcis-2135	57	3	trajectory	trajectory	NOUN
fcis-2135	57	4	of	of	ADP
fcis-2135	57	5	pedestrians	pedestrian	NOUN
fcis-2135	57	6	is	be	AUX
fcis-2135	57	7	not	not	PART
fcis-2135	57	8	only	only	ADV
fcis-2135	57	9	affected	affect	VERB
fcis-2135	57	10	by	by	ADP
fcis-2135	57	11	the	the	DET
fcis-2135	57	12	surrounding	surround	VERB
fcis-2135	57	13	pedestrians	pedestrian	NOUN
fcis-2135	57	14	,	,	PUNCT
fcis-2135	57	15	but	but	CCONJ
fcis-2135	57	16	also	also	ADV
fcis-2135	57	17	by	by	ADP
fcis-2135	57	18	the	the	DET
fcis-2135	57	19	scene	scene	NOUN
fcis-2135	57	20	environment	environment	NOUN
fcis-2135	57	21	,	,	PUNCT
fcis-2135	57	22	the	the	DET
fcis-2135	57	23	methods	method	NOUN
fcis-2135	57	24	based	base	VERB
fcis-2135	57	25	on	on	ADP
fcis-2135	57	26	scene	scene	NOUN
fcis-2135	57	27	interaction	interaction	NOUN
fcis-2135	57	28	mainly	mainly	ADV
fcis-2135	57	29	include	include	VERB
fcis-2135	57	30	static	static	ADJ
fcis-2135	57	31	obstacle	obstacle	NOUN
fcis-2135	57	32	avoidance	avoidance	NOUN
fcis-2135	57	33	method	method	NOUN
fcis-2135	57	34	[	[	X
fcis-2135	57	35	11	11	NUM
fcis-2135	57	36	]	]	PUNCT
fcis-2135	57	37	,	,	PUNCT
fcis-2135	57	38	map	map	VERB
fcis-2135	57	39	perception	perception	NOUN
fcis-2135	57	40	method	method	NOUN
fcis-2135	57	41	[	[	X
fcis-2135	57	42	12	12	NUM
fcis-2135	57	43	]	]	PUNCT
fcis-2135	57	44	and	and	CCONJ
fcis-2135	57	45	semantic	semantic	ADJ
fcis-2135	57	46	graph	graph	NOUN
fcis-2135	57	47	method	method	NOUN
fcis-2135	57	48	[	[	X
fcis-2135	57	49	13	13	NUM
fcis-2135	57	50	-	-	SYM
fcis-2135	57	51	16	16	NUM
fcis-2135	57	52	]	]	PUNCT
fcis-2135	57	53	,	,	PUNCT
fcis-2135	57	54	which	which	PRON
fcis-2135	57	55	can	can	AUX
fcis-2135	57	56	improve	improve	VERB
fcis-2135	57	57	the	the	DET
fcis-2135	57	58	prediction	prediction	NOUN
fcis-2135	57	59	performance	performance	NOUN
fcis-2135	57	60	of	of	ADP
fcis-2135	57	61	pedestrian	pedestrian	NOUN
fcis-2135	57	62	trajectory	trajectory	NOUN
fcis-2135	57	63	to	to	ADP
fcis-2135	57	64	a	a	DET
fcis-2135	57	65	certain	certain	ADJ
fcis-2135	57	66	extent	extent	NOUN
fcis-2135	57	67	.	.	PUNCT
fcis-2135	58	1	specifically	specifically	ADV
fcis-2135	58	2	,	,	PUNCT
fcis-2135	58	3	the	the	DET
fcis-2135	58	4	processing	processing	NOUN
fcis-2135	58	5	flow	flow	NOUN
fcis-2135	58	6	of	of	ADP
fcis-2135	58	7	typical	typical	ADJ
fcis-2135	58	8	pedestrian	pedestrian	NOUN
fcis-2135	58	9	trajectory	trajectory	NOUN
fcis-2135	58	10	prediction	prediction	NOUN
fcis-2135	58	11	problems	problem	NOUN
fcis-2135	58	12	includes	include	VERB
fcis-2135	58	13	:	:	PUNCT
fcis-2135	58	14	pre	pre	ADJ
fcis-2135	58	15	-	-	ADJ
fcis-2135	58	16	dataset	dataset	ADJ
fcis-2135	58	17	collection	collection	NOUN
fcis-2135	58	18	,	,	PUNCT
fcis-2135	58	19	dataset	dataset	NOUN
fcis-2135	58	20	preprocessing	preprocessing	NOUN
fcis-2135	58	21	and	and	CCONJ
fcis-2135	58	22	input	input	NOUN
fcis-2135	58	23	,	,	PUNCT
fcis-2135	58	24	feature	feature	NOUN
fcis-2135	58	25	coding	coding	NOUN
fcis-2135	58	26	,	,	PUNCT
fcis-2135	58	27	extraction	extraction	NOUN
fcis-2135	58	28	and	and	CCONJ
fcis-2135	58	29	aggregation	aggregation	NOUN
fcis-2135	58	30	,	,	PUNCT
fcis-2135	58	31	trajectory	trajectory	NOUN
fcis-2135	58	32	prediction	prediction	NOUN
fcis-2135	58	33	visualization	visualization	NOUN
fcis-2135	58	34	and	and	CCONJ
fcis-2135	58	35	prediction	prediction	NOUN
fcis-2135	58	36	result	result	NOUN
fcis-2135	58	37	output	output	NOUN
fcis-2135	58	38	,	,	PUNCT
fcis-2135	58	39	as	as	SCONJ
fcis-2135	58	40	shown	show	VERB
fcis-2135	58	41	in	in	ADP
fcis-2135	58	42	figure	figure	NOUN
fcis-2135	58	43	1	1	NUM
fcis-2135	58	44	.	.	PUNCT
fcis-2135	58	45	fig	fig	NOUN
fcis-2135	58	46	.	.	PUNCT
fcis-2135	59	1	1	1	NUM
fcis-2135	59	2	process	process	NOUN
fcis-2135	59	3	of	of	ADP
fcis-2135	59	4	pedestrian	pedestrian	NOUN
fcis-2135	59	5	trajectory	trajectory	NOUN
fcis-2135	59	6	prediction	prediction	NOUN
fcis-2135	59	7	problem	problem	NOUN
fcis-2135	59	8	2.2	2.2	NUM
fcis-2135	59	9	.	.	PUNCT
fcis-2135	60	1	introduction	introduction	NOUN
fcis-2135	60	2	of	of	ADP
fcis-2135	60	3	pedestrian	pedestrian	NOUN
fcis-2135	60	4	trajectory	trajectory	NOUN
fcis-2135	60	5	prediction	prediction	NOUN
fcis-2135	60	6	method	method	NOUN
fcis-2135	60	7	pedestrian	pedestrian	NOUN
fcis-2135	60	8	trajectory	trajectory	NOUN
fcis-2135	60	9	prediction	prediction	NOUN
fcis-2135	60	10	methods	method	NOUN
fcis-2135	60	11	can	can	AUX
fcis-2135	60	12	be	be	AUX
fcis-2135	60	13	roughly	roughly	ADV
fcis-2135	60	14	divided	divide	VERB
fcis-2135	60	15	into	into	ADP
fcis-2135	60	16	methods	method	NOUN
fcis-2135	60	17	based	base	VERB
fcis-2135	60	18	on	on	ADP
fcis-2135	60	19	traditional	traditional	ADJ
fcis-2135	60	20	probability	probability	NOUN
fcis-2135	60	21	prediction	prediction	NOUN
fcis-2135	60	22	and	and	CCONJ
fcis-2135	60	23	methods	method	NOUN
fcis-2135	60	24	based	base	VERB
fcis-2135	60	25	on	on	ADP
fcis-2135	60	26	deep	deep	ADJ
fcis-2135	60	27	learning	learning	NOUN
fcis-2135	60	28	.	.	PUNCT
fcis-2135	61	1	based	base	VERB
fcis-2135	61	2	on	on	ADP
fcis-2135	61	3	the	the	DET
fcis-2135	61	4	traditional	traditional	ADJ
fcis-2135	61	5	probability	probability	NOUN
fcis-2135	61	6	prediction	prediction	NOUN
fcis-2135	61	7	method	method	NOUN
fcis-2135	61	8	,	,	PUNCT
fcis-2135	61	9	the	the	DET
fcis-2135	61	10	pedestrian	pedestrian	NOUN
fcis-2135	61	11	prediction	prediction	NOUN
fcis-2135	61	12	is	be	AUX
fcis-2135	61	13	transformed	transform	VERB
fcis-2135	61	14	into	into	ADP
fcis-2135	61	15	a	a	DET
fcis-2135	61	16	probability	probability	NOUN
fcis-2135	61	17	prediction	prediction	NOUN
fcis-2135	61	18	problem	problem	NOUN
fcis-2135	61	19	.	.	PUNCT
fcis-2135	62	1	the	the	DET
fcis-2135	62	2	pedestrian	pedestrian	NOUN
fcis-2135	62	3	kinematics	kinematic	NOUN
fcis-2135	62	4	model	model	NOUN
fcis-2135	62	5	is	be	AUX
fcis-2135	62	6	established	establish	VERB
fcis-2135	62	7	to	to	PART
fcis-2135	62	8	estimate	estimate	VERB
fcis-2135	62	9	the	the	DET
fcis-2135	62	10	change	change	NOUN
fcis-2135	62	11	of	of	ADP
fcis-2135	62	12	pedestrian	pedestrian	NOUN
fcis-2135	62	13	motion	motion	NOUN
fcis-2135	62	14	state	state	NOUN
fcis-2135	62	15	with	with	ADP
fcis-2135	62	16	time	time	NOUN
fcis-2135	62	17	,	,	PUNCT
fcis-2135	62	18	so	so	SCONJ
fcis-2135	62	19	as	as	SCONJ
fcis-2135	62	20	to	to	PART
fcis-2135	62	21	obtain	obtain	VERB
fcis-2135	62	22	the	the	DET
fcis-2135	62	23	pedestrian	pedestrian	NOUN
fcis-2135	62	24	trajectory	trajectory	NOUN
fcis-2135	62	25	results	result	NOUN
fcis-2135	62	26	.	.	PUNCT
fcis-2135	63	1	nicolas	nicolas	PROPN
fcis-2135	63	2	schneider	schneider	PROPN
fcis-2135	63	3	et	et	PROPN
fcis-2135	63	4	al	al	PROPN
fcis-2135	63	5	.	.	PUNCT
fcis-2135	64	1	[	[	X
fcis-2135	64	2	17	17	NUM
fcis-2135	64	3	]	]	PUNCT
fcis-2135	64	4	used	use	VERB
fcis-2135	64	5	dynamic	dynamic	ADJ
fcis-2135	64	6	bayesian	bayesian	NOUN
fcis-2135	64	7	network	network	NOUN
fcis-2135	64	8	to	to	PART
fcis-2135	64	9	determine	determine	VERB
fcis-2135	64	10	the	the	DET
fcis-2135	64	11	trajectory	trajectory	NOUN
fcis-2135	64	12	of	of	ADP
fcis-2135	64	13	pedestrians	pedestrian	NOUN
fcis-2135	64	14	according	accord	VERB
fcis-2135	64	15	to	to	ADP
fcis-2135	64	16	the	the	DET
fcis-2135	64	17	head	head	NOUN
fcis-2135	64	18	posture	posture	NOUN
fcis-2135	64	19	of	of	ADP
fcis-2135	64	20	pedestrians	pedestrian	NOUN
fcis-2135	64	21	,	,	PUNCT
fcis-2135	64	22	the	the	DET
fcis-2135	64	23	nearest	near	ADJ
fcis-2135	64	24	collision	collision	NOUN
fcis-2135	64	25	point	point	NOUN
fcis-2135	64	26	between	between	ADP
fcis-2135	64	27	pedestrians	pedestrian	NOUN
fcis-2135	64	28	and	and	CCONJ
fcis-2135	64	29	vehicles	vehicle	NOUN
fcis-2135	64	30	,	,	PUNCT
fcis-2135	64	31	and	and	CCONJ
fcis-2135	64	32	the	the	DET
fcis-2135	64	33	distance	distance	NOUN
fcis-2135	64	34	between	between	ADP
fcis-2135	64	35	pedestrians	pedestrian	NOUN
fcis-2135	64	36	and	and	CCONJ
fcis-2135	64	37	roadsides	roadside	NOUN
fcis-2135	64	38	when	when	SCONJ
fcis-2135	64	39	the	the	DET
fcis-2135	64	40	scene	scene	NOUN
fcis-2135	64	41	is	be	AUX
fcis-2135	64	42	relatively	relatively	ADV
fcis-2135	64	43	certain	certain	ADJ
fcis-2135	64	44	,	,	PUNCT
fcis-2135	64	45	that	that	ADV
fcis-2135	64	46	is	is	ADV
fcis-2135	64	47	,	,	PUNCT
fcis-2135	64	48	pedestrians	pedestrian	NOUN
fcis-2135	64	49	are	be	AUX
fcis-2135	64	50	ready	ready	ADJ
fcis-2135	64	51	to	to	PART
fcis-2135	64	52	cross	cross	VERB
fcis-2135	64	53	the	the	DET
fcis-2135	64	54	road	road	NOUN
fcis-2135	64	55	.	.	PUNCT
fcis-2135	65	1	qm	qm	PROPN
fcis-2135	65	2	raul	raul	PROPN
fcis-2135	65	3	et	et	PROPN
fcis-2135	65	4	al	al	PROPN
fcis-2135	65	5	.	.	PUNCT
fcis-2135	66	1	[	[	X
fcis-2135	66	2	18	18	NUM
fcis-2135	66	3	]	]	PUNCT
fcis-2135	66	4	extracted	extract	VERB
fcis-2135	66	5	the	the	DET
fcis-2135	66	6	three	three	NUM
fcis-2135	66	7	-	-	PUNCT
fcis-2135	66	8	dimensional	dimensional	ADJ
fcis-2135	66	9	time	time	NOUN
fcis-2135	66	10	-	-	PUNCT
fcis-2135	66	11	related	relate	VERB
fcis-2135	66	12	information	information	NOUN
fcis-2135	66	13	of	of	ADP
fcis-2135	66	14	the	the	DET
fcis-2135	66	15	key	key	ADJ
fcis-2135	66	16	points	point	NOUN
fcis-2135	66	17	of	of	ADP
fcis-2135	66	18	the	the	DET
fcis-2135	66	19	pedestrian	pedestrian	NOUN
fcis-2135	66	20	skeleton	skeleton	NOUN
fcis-2135	66	21	into	into	ADP
fcis-2135	66	22	a	a	DET
fcis-2135	66	23	lowdimensional	lowdimensional	ADJ
fcis-2135	66	24	space	space	NOUN
fcis-2135	66	25	based	base	VERB
fcis-2135	66	26	on	on	ADP
fcis-2135	66	27	the	the	DET
fcis-2135	66	28	balanced	balanced	ADJ
fcis-2135	66	29	gaussian	gaussian	ADJ
fcis-2135	66	30	process	process	NOUN
fcis-2135	66	31	dynamics	dynamic	NOUN
fcis-2135	66	32	model	model	NOUN
fcis-2135	66	33	(	(	PUNCT
fcis-2135	66	34	b	b	NOUN
fcis-2135	66	35	-	-	PUNCT
fcis-2135	66	36	gpdms	gpdms	NOUN
fcis-2135	66	37	)	)	PUNCT
fcis-2135	66	38	,	,	PUNCT
fcis-2135	66	39	and	and	CCONJ
fcis-2135	66	40	obtained	obtain	VERB
fcis-2135	66	41	multiple	multiple	ADJ
fcis-2135	66	42	models	model	NOUN
fcis-2135	66	43	of	of	ADP
fcis-2135	66	44	the	the	DET
fcis-2135	66	45	four	four	NUM
fcis-2135	66	46	behaviors	behavior	NOUN
fcis-2135	66	47	of	of	ADP
fcis-2135	66	48	pedestrian	pedestrian	NOUN
fcis-2135	66	49	walking	walking	NOUN
fcis-2135	66	50	,	,	PUNCT
fcis-2135	66	51	stopping	stop	VERB
fcis-2135	66	52	,	,	PUNCT
fcis-2135	66	53	starting	starting	NOUN
fcis-2135	66	54	and	and	CCONJ
fcis-2135	66	55	standing	stand	VERB
fcis-2135	66	56	during	during	ADP
fcis-2135	66	57	use	use	NOUN
fcis-2135	66	58	,	,	PUNCT
fcis-2135	66	59	and	and	CCONJ
fcis-2135	66	60	selected	select	VERB
fcis-2135	66	61	the	the	DET
fcis-2135	66	62	most	most	ADV
fcis-2135	66	63	similar	similar	ADJ
fcis-2135	66	64	model	model	NOUN
fcis-2135	66	65	to	to	PART
fcis-2135	66	66	predict	predict	VERB
fcis-2135	66	67	the	the	DET
fcis-2135	66	68	future	future	ADJ
fcis-2135	66	69	path	path	NOUN
fcis-2135	66	70	,	,	PUNCT
fcis-2135	66	71	posture	posture	NOUN
fcis-2135	66	72	and	and	CCONJ
fcis-2135	66	73	intention	intention	NOUN
fcis-2135	66	74	of	of	ADP
fcis-2135	66	75	pedestrians	pedestrian	NOUN
fcis-2135	66	76	.	.	PUNCT
fcis-2135	67	1	however	however	ADV
fcis-2135	67	2	,	,	PUNCT
fcis-2135	67	3	these	these	DET
fcis-2135	67	4	methods	method	NOUN
fcis-2135	67	5	can	can	AUX
fcis-2135	67	6	not	not	PART
fcis-2135	67	7	capture	capture	VERB
fcis-2135	67	8	the	the	DET
fcis-2135	67	9	complex	complex	ADJ
fcis-2135	67	10	and	and	CCONJ
fcis-2135	67	11	changeable	changeable	ADJ
fcis-2135	67	12	motion	motion	NOUN
fcis-2135	67	13	characteristics	characteristic	NOUN
fcis-2135	67	14	and	and	CCONJ
fcis-2135	67	15	rich	rich	ADJ
fcis-2135	67	16	environmental	environmental	ADJ
fcis-2135	67	17	characteristics	characteristic	NOUN
fcis-2135	67	18	of	of	ADP
fcis-2135	67	19	pedestrians	pedestrian	NOUN
fcis-2135	67	20	in	in	ADP
fcis-2135	67	21	practical	practical	ADJ
fcis-2135	67	22	use	use	NOUN
fcis-2135	67	23	,	,	PUNCT
fcis-2135	67	24	and	and	CCONJ
fcis-2135	67	25	are	be	AUX
fcis-2135	67	26	sensitive	sensitive	ADJ
fcis-2135	67	27	to	to	ADP
fcis-2135	67	28	input	input	NOUN
fcis-2135	67	29	noise	noise	NOUN
fcis-2135	67	30	.	.	PUNCT
fcis-2135	68	1	they	they	PRON
fcis-2135	68	2	can	can	AUX
fcis-2135	68	3	only	only	ADV
fcis-2135	68	4	obtain	obtain	VERB
fcis-2135	68	5	the	the	DET
fcis-2135	68	6	prediction	prediction	NOUN
fcis-2135	68	7	results	result	NOUN
fcis-2135	68	8	in	in	ADP
fcis-2135	68	9	a	a	DET
fcis-2135	68	10	short	short	ADJ
fcis-2135	68	11	time	time	NOUN
fcis-2135	68	12	range	range	NOUN
fcis-2135	68	13	,	,	PUNCT
fcis-2135	68	14	which	which	PRON
fcis-2135	68	15	has	have	VERB
fcis-2135	68	16	great	great	ADJ
fcis-2135	68	17	problems	problem	NOUN
fcis-2135	68	18	in	in	ADP
fcis-2135	68	19	practical	practical	ADJ
fcis-2135	68	20	use	use	NOUN
fcis-2135	68	21	.	.	PUNCT
fcis-2135	69	1	with	with	ADP
fcis-2135	69	2	the	the	DET
fcis-2135	69	3	continuous	continuous	ADJ
fcis-2135	69	4	development	development	NOUN
fcis-2135	69	5	of	of	ADP
fcis-2135	69	6	deep	deep	ADJ
fcis-2135	69	7	learning	learning	NOUN
fcis-2135	69	8	,	,	PUNCT
fcis-2135	69	9	researchers	researcher	NOUN
fcis-2135	69	10	began	begin	VERB
fcis-2135	69	11	to	to	PART
fcis-2135	69	12	introduce	introduce	VERB
fcis-2135	69	13	deep	deep	ADJ
fcis-2135	69	14	learning	learning	NOUN
fcis-2135	69	15	methods	method	NOUN
fcis-2135	69	16	into	into	ADP
fcis-2135	69	17	pedestrian	pedestrian	NOUN
fcis-2135	69	18	trajectory	trajectory	NOUN
fcis-2135	69	19	prediction	prediction	NOUN
fcis-2135	69	20	tasks	task	NOUN
fcis-2135	69	21	.	.	PUNCT
fcis-2135	70	1	at	at	ADP
fcis-2135	70	2	present	present	ADJ
fcis-2135	70	3	,	,	PUNCT
fcis-2135	70	4	the	the	DET
fcis-2135	70	5	common	common	ADJ
fcis-2135	70	6	pedestrian	pedestrian	NOUN
fcis-2135	70	7	trajectory	trajectory	NOUN
fcis-2135	70	8	prediction	prediction	NOUN
fcis-2135	70	9	methods	method	NOUN
fcis-2135	70	10	based	base	VERB
fcis-2135	70	11	on	on	ADP
fcis-2135	70	12	deep	deep	ADJ
fcis-2135	70	13	learning	learning	NOUN
fcis-2135	70	14	mainly	mainly	ADV
fcis-2135	70	15	include	include	VERB
fcis-2135	70	16	rnn	rnn	NOUN
fcis-2135	70	17	-	-	PUNCT
fcis-2135	70	18	based	base	VERB
fcis-2135	70	19	pedestrian	pedestrian	NOUN
fcis-2135	70	20	trajectory	trajectory	NOUN
fcis-2135	70	21	prediction	prediction	NOUN
fcis-2135	70	22	,	,	PUNCT
fcis-2135	70	23	gan	gan	NOUN
fcis-2135	70	24	-	-	PUNCT
fcis-2135	70	25	based	base	VERB
fcis-2135	70	26	pedestrian	pedestrian	NOUN
fcis-2135	70	27	trajectory	trajectory	NOUN
fcis-2135	70	28	prediction	prediction	NOUN
fcis-2135	70	29	and	and	CCONJ
fcis-2135	70	30	gcn	gcn	NOUN
fcis-2135	70	31	-	-	PUNCT
fcis-2135	70	32	based	base	VERB
fcis-2135	70	33	pedestrian	pedestrian	NOUN
fcis-2135	70	34	trajectory	trajectory	NOUN
fcis-2135	70	35	prediction	prediction	NOUN
fcis-2135	70	36	.	.	PUNCT
fcis-2135	71	1	pedestrian	pedestrian	NOUN
fcis-2135	71	2	trajectory	trajectory	NOUN
fcis-2135	71	3	prediction	prediction	NOUN
fcis-2135	71	4	based	base	VERB
fcis-2135	71	5	on	on	ADP
fcis-2135	71	6	rnn	rnn	PROPN
fcis-2135	71	7	.	.	PUNCT
fcis-2135	72	1	the	the	DET
fcis-2135	72	2	recurrent	recurrent	ADJ
fcis-2135	72	3	neural	neural	ADJ
fcis-2135	72	4	network	network	NOUN
fcis-2135	72	5	rnn	rnn	NOUN
fcis-2135	72	6	is	be	AUX
fcis-2135	72	7	the	the	DET
fcis-2135	72	8	earliest	early	ADJ
fcis-2135	72	9	model	model	NOUN
fcis-2135	72	10	for	for	ADP
fcis-2135	72	11	pedestrian	pedestrian	NOUN
fcis-2135	72	12	trajectory	trajectory	NOUN
fcis-2135	72	13	prediction	prediction	NOUN
fcis-2135	72	14	.	.	PUNCT
fcis-2135	73	1	it	it	PRON
fcis-2135	73	2	determines	determine	VERB
fcis-2135	73	3	the	the	DET
fcis-2135	73	4	output	output	NOUN
fcis-2135	73	5	by	by	ADP
fcis-2135	73	6	inputting	inputte	VERB
fcis-2135	73	7	and	and	CCONJ
fcis-2135	73	8	storing	store	VERB
fcis-2135	73	9	information	information	NOUN
fcis-2135	73	10	in	in	ADP
fcis-2135	73	11	the	the	DET
fcis-2135	73	12	historical	historical	ADJ
fcis-2135	73	13	network	network	NOUN
fcis-2135	73	14	.	.	PUNCT
fcis-2135	74	1	through	through	ADP
fcis-2135	74	2	this	this	DET
fcis-2135	74	3	feature	feature	NOUN
fcis-2135	74	4	,	,	PUNCT
fcis-2135	74	5	rnn	rnn	PROPN
fcis-2135	74	6	can	can	AUX
fcis-2135	74	7	predict	predict	VERB
fcis-2135	74	8	future	future	ADJ
fcis-2135	74	9	values	value	NOUN
fcis-2135	74	10	based	base	VERB
fcis-2135	74	11	on	on	ADP
fcis-2135	74	12	historical	historical	ADJ
fcis-2135	74	13	sequence	sequence	NOUN
fcis-2135	74	14	information	information	NOUN
fcis-2135	74	15	.	.	PUNCT
fcis-2135	75	1	it	it	PRON
fcis-2135	75	2	can	can	AUX
fcis-2135	75	3	be	be	AUX
fcis-2135	75	4	said	say	VERB
fcis-2135	75	5	that	that	SCONJ
fcis-2135	75	6	rnn	rnn	PROPN
fcis-2135	75	7	is	be	AUX
fcis-2135	75	8	designed	design	VERB
fcis-2135	75	9	for	for	ADP
fcis-2135	75	10	sequence	sequence	NOUN
fcis-2135	75	11	modeling	modeling	NOUN
fcis-2135	75	12	and	and	CCONJ
fcis-2135	75	13	has	have	VERB
fcis-2135	75	14	a	a	DET
fcis-2135	75	15	recursive	recursive	ADJ
fcis-2135	75	16	organizational	organizational	ADJ
fcis-2135	75	17	structure	structure	NOUN
fcis-2135	75	18	,	,	PUNCT
fcis-2135	75	19	showing	show	VERB
fcis-2135	75	20	strong	strong	ADJ
fcis-2135	75	21	modeling	modeling	NOUN
fcis-2135	75	22	capabilities	capability	NOUN
fcis-2135	75	23	in	in	ADP
fcis-2135	75	24	time	time	NOUN
fcis-2135	75	25	analysis	analysis	NOUN
fcis-2135	75	26	and	and	CCONJ
fcis-2135	75	27	sequence	sequence	NOUN
fcis-2135	75	28	learning	learning	NOUN
fcis-2135	75	29	.	.	PUNCT
fcis-2135	76	1	however	however	ADV
fcis-2135	76	2	,	,	PUNCT
fcis-2135	76	3	as	as	ADP
fcis-2135	76	4	the	the	DET
fcis-2135	76	5	length	length	NOUN
fcis-2135	76	6	of	of	ADP
fcis-2135	76	7	the	the	DET
fcis-2135	76	8	time	time	NOUN
fcis-2135	76	9	series	series	NOUN
fcis-2135	76	10	increases	increase	VERB
fcis-2135	76	11	,	,	PUNCT
fcis-2135	76	12	the	the	DET
fcis-2135	76	13	shortcomings	shortcoming	NOUN
fcis-2135	76	14	of	of	ADP
fcis-2135	76	15	rnn	rnn	NOUN
fcis-2135	76	16	gradually	gradually	ADV
fcis-2135	76	17	emerge	emerge	VERB
fcis-2135	76	18	.	.	PUNCT
fcis-2135	77	1	rnn	rnn	PROPN
fcis-2135	77	2	can	can	AUX
fcis-2135	77	3	not	not	PART
fcis-2135	77	4	achieve	achieve	VERB
fcis-2135	77	5	long	long	ADJ
fcis-2135	77	6	-	-	PUNCT
fcis-2135	77	7	term	term	NOUN
fcis-2135	77	8	memory	memory	NOUN
fcis-2135	77	9	of	of	ADP
fcis-2135	77	10	the	the	DET
fcis-2135	77	11	data	datum	NOUN
fcis-2135	77	12	state	state	NOUN
fcis-2135	77	13	,	,	PUNCT
fcis-2135	77	14	resulting	result	VERB
fcis-2135	77	15	in	in	ADP
fcis-2135	77	16	the	the	DET
fcis-2135	77	17	network	network	NOUN
fcis-2135	77	18	layer	layer	NOUN
fcis-2135	77	19	stopping	stop	VERB
fcis-2135	77	20	learning	learning	NOUN
fcis-2135	77	21	.	.	PUNCT
fcis-2135	78	1	in	in	ADP
fcis-2135	78	2	terms	term	NOUN
fcis-2135	78	3	of	of	ADP
fcis-2135	78	4	effectiveness	effectiveness	NOUN
fcis-2135	78	5	,	,	PUNCT
fcis-2135	78	6	rnn	rnn	PROPN
fcis-2135	78	7	will	will	AUX
fcis-2135	78	8	store	store	VERB
fcis-2135	78	9	all	all	DET
fcis-2135	78	10	historical	historical	ADJ
fcis-2135	78	11	information	information	NOUN
fcis-2135	78	12	in	in	ADP
fcis-2135	78	13	the	the	DET
fcis-2135	78	14	network	network	NOUN
fcis-2135	78	15	,	,	PUNCT
fcis-2135	78	16	which	which	PRON
fcis-2135	78	17	will	will	AUX
fcis-2135	78	18	lead	lead	VERB
fcis-2135	78	19	to	to	ADP
fcis-2135	78	20	70	70	NUM
fcis-2135	78	21	gradient	gradient	NOUN
fcis-2135	78	22	disappearance	disappearance	NOUN
fcis-2135	78	23	or	or	CCONJ
fcis-2135	78	24	gradient	gradient	ADJ
fcis-2135	78	25	explosion	explosion	NOUN
fcis-2135	78	26	in	in	ADP
fcis-2135	78	27	large	large	ADJ
fcis-2135	78	28	networks	network	NOUN
fcis-2135	78	29	during	during	ADP
fcis-2135	78	30	training	training	NOUN
fcis-2135	78	31	.	.	PUNCT
fcis-2135	79	1	in	in	ADP
fcis-2135	79	2	terms	term	NOUN
fcis-2135	79	3	of	of	ADP
fcis-2135	79	4	operating	operate	VERB
fcis-2135	79	5	efficiency	efficiency	NOUN
fcis-2135	79	6	,	,	PUNCT
fcis-2135	79	7	because	because	SCONJ
fcis-2135	79	8	the	the	DET
fcis-2135	79	9	current	current	ADJ
fcis-2135	79	10	state	state	NOUN
fcis-2135	79	11	of	of	ADP
fcis-2135	79	12	the	the	DET
fcis-2135	79	13	rnn	rnn	NOUN
fcis-2135	79	14	model	model	NOUN
fcis-2135	79	15	depends	depend	VERB
fcis-2135	79	16	on	on	ADP
fcis-2135	79	17	the	the	DET
fcis-2135	79	18	hidden	hidden	ADJ
fcis-2135	79	19	state	state	NOUN
fcis-2135	79	20	of	of	ADP
fcis-2135	79	21	the	the	DET
fcis-2135	79	22	previous	previous	ADJ
fcis-2135	79	23	moment	moment	NOUN
fcis-2135	79	24	,	,	PUNCT
fcis-2135	79	25	parallel	parallel	ADJ
fcis-2135	79	26	processing	processing	NOUN
fcis-2135	79	27	can	can	AUX
fcis-2135	79	28	not	not	PART
fcis-2135	79	29	be	be	AUX
fcis-2135	79	30	realized	realize	VERB
fcis-2135	79	31	,	,	PUNCT
fcis-2135	79	32	resulting	result	VERB
fcis-2135	79	33	in	in	ADP
fcis-2135	79	34	low	low	ADJ
fcis-2135	79	35	training	training	NOUN
fcis-2135	79	36	and	and	CCONJ
fcis-2135	79	37	reasoning	reasoning	NOUN
fcis-2135	79	38	speed	speed	NOUN
fcis-2135	79	39	of	of	ADP
fcis-2135	79	40	the	the	DET
fcis-2135	79	41	model	model	NOUN
fcis-2135	79	42	.	.	PUNCT
fcis-2135	80	1	in	in	ADP
fcis-2135	80	2	pedestrian	pedestrian	NOUN
fcis-2135	80	3	trajectory	trajectory	NOUN
fcis-2135	80	4	prediction	prediction	NOUN
fcis-2135	80	5	,	,	PUNCT
fcis-2135	80	6	a	a	DET
fcis-2135	80	7	large	large	ADJ
fcis-2135	80	8	number	number	NOUN
fcis-2135	80	9	of	of	ADP
fcis-2135	80	10	network	network	NOUN
fcis-2135	80	11	nodes	node	NOUN
fcis-2135	80	12	and	and	CCONJ
fcis-2135	80	13	huge	huge	ADJ
fcis-2135	80	14	data	data	NOUN
fcis-2135	80	15	sets	set	NOUN
fcis-2135	80	16	are	be	AUX
fcis-2135	80	17	needed	need	VERB
fcis-2135	80	18	to	to	PART
fcis-2135	80	19	train	train	VERB
fcis-2135	80	20	the	the	DET
fcis-2135	80	21	network	network	NOUN
fcis-2135	80	22	to	to	PART
fcis-2135	80	23	improve	improve	VERB
fcis-2135	80	24	the	the	DET
fcis-2135	80	25	accuracy	accuracy	NOUN
fcis-2135	80	26	of	of	ADP
fcis-2135	80	27	prediction	prediction	NOUN
fcis-2135	80	28	.	.	PUNCT
fcis-2135	81	1	therefore	therefore	ADV
fcis-2135	81	2	,	,	PUNCT
fcis-2135	81	3	the	the	DET
fcis-2135	81	4	traditional	traditional	ADJ
fcis-2135	81	5	rnn	rnn	NOUN
fcis-2135	81	6	will	will	AUX
fcis-2135	81	7	not	not	PART
fcis-2135	81	8	meet	meet	VERB
fcis-2135	81	9	the	the	DET
fcis-2135	81	10	needs	need	NOUN
fcis-2135	81	11	of	of	ADP
fcis-2135	81	12	pedestrian	pedestrian	NOUN
fcis-2135	81	13	trajectory	trajectory	NOUN
fcis-2135	81	14	prediction	prediction	NOUN
fcis-2135	81	15	.	.	PUNCT
fcis-2135	82	1	however	however	ADV
fcis-2135	82	2	,	,	PUNCT
fcis-2135	82	3	researchers	researcher	NOUN
fcis-2135	82	4	have	have	AUX
fcis-2135	82	5	developed	develop	VERB
fcis-2135	82	6	related	related	ADJ
fcis-2135	82	7	variants	variant	NOUN
fcis-2135	82	8	based	base	VERB
fcis-2135	82	9	on	on	ADP
fcis-2135	82	10	rnn	rnn	NOUN
fcis-2135	82	11	networks	network	NOUN
fcis-2135	82	12	,	,	PUNCT
fcis-2135	82	13	such	such	ADJ
fcis-2135	82	14	as	as	ADP
fcis-2135	82	15	long	long	ADJ
fcis-2135	82	16	short	short	ADJ
fcis-2135	82	17	-	-	PUNCT
fcis-2135	82	18	term	term	NOUN
fcis-2135	82	19	memory	memory	NOUN
fcis-2135	82	20	networks	network	NOUN
fcis-2135	82	21	(	(	PUNCT
fcis-2135	82	22	lstm	lstm	NOUN
fcis-2135	82	23	)	)	PUNCT
fcis-2135	82	24	and	and	CCONJ
fcis-2135	82	25	gate	gate	NOUN
fcis-2135	82	26	cycle	cycle	NOUN
fcis-2135	82	27	units	unit	NOUN
fcis-2135	82	28	(	(	PUNCT
fcis-2135	82	29	grus	grus	NOUN
fcis-2135	82	30	)	)	PUNCT
fcis-2135	82	31	,	,	PUNCT
fcis-2135	82	32	which	which	PRON
fcis-2135	82	33	regulate	regulate	VERB
fcis-2135	82	34	the	the	DET
fcis-2135	82	35	flow	flow	NOUN
fcis-2135	82	36	and	and	CCONJ
fcis-2135	82	37	selection	selection	NOUN
fcis-2135	82	38	of	of	ADP
fcis-2135	82	39	information	information	NOUN
fcis-2135	82	40	through	through	ADP
fcis-2135	82	41	gating	gate	VERB
fcis-2135	82	42	mechanisms	mechanism	NOUN
fcis-2135	82	43	to	to	PART
fcis-2135	82	44	solve	solve	VERB
fcis-2135	82	45	the	the	DET
fcis-2135	82	46	problem	problem	NOUN
fcis-2135	82	47	of	of	ADP
fcis-2135	82	48	information	information	NOUN
fcis-2135	82	49	transmission	transmission	NOUN
fcis-2135	82	50	in	in	ADP
fcis-2135	82	51	long	long	ADJ
fcis-2135	82	52	sequences	sequence	NOUN
fcis-2135	82	53	.	.	PUNCT
fcis-2135	83	1	in	in	ADP
fcis-2135	83	2	the	the	DET
fcis-2135	83	3	field	field	NOUN
fcis-2135	83	4	of	of	ADP
fcis-2135	83	5	pedestrian	pedestrian	NOUN
fcis-2135	83	6	trajectory	trajectory	NOUN
fcis-2135	83	7	prediction	prediction	NOUN
fcis-2135	83	8	,	,	PUNCT
fcis-2135	83	9	the	the	DET
fcis-2135	83	10	above	above	ADJ
fcis-2135	83	11	variant	variant	ADJ
fcis-2135	83	12	methods	method	NOUN
fcis-2135	83	13	have	have	AUX
fcis-2135	83	14	focused	focus	VERB
fcis-2135	83	15	on	on	ADP
fcis-2135	83	16	rnn	rnn	NOUN
fcis-2135	83	17	research	research	NOUN
fcis-2135	83	18	and	and	CCONJ
fcis-2135	83	19	achieved	achieve	VERB
fcis-2135	83	20	remarkable	remarkable	ADJ
fcis-2135	83	21	success	success	NOUN
fcis-2135	83	22	[	[	X
fcis-2135	83	23	19	19	NUM
fcis-2135	83	24	-	-	SYM
fcis-2135	83	25	22	22	NUM
fcis-2135	83	26	]	]	PUNCT
fcis-2135	83	27	.	.	PUNCT
fcis-2135	84	1	pedestrian	pedestrian	NOUN
fcis-2135	84	2	trajectory	trajectory	NOUN
fcis-2135	84	3	prediction	prediction	NOUN
fcis-2135	84	4	based	base	VERB
fcis-2135	84	5	on	on	ADP
fcis-2135	84	6	gcn	gcn	PROPN
fcis-2135	84	7	.	.	PUNCT
fcis-2135	85	1	the	the	DET
fcis-2135	85	2	graph	graph	NOUN
fcis-2135	85	3	convolutional	convolutional	ADJ
fcis-2135	85	4	neural	neural	ADJ
fcis-2135	85	5	network	network	NOUN
fcis-2135	85	6	gcn	gcn	NOUN
fcis-2135	85	7	is	be	AUX
fcis-2135	85	8	a	a	DET
fcis-2135	85	9	method	method	NOUN
fcis-2135	85	10	that	that	PRON
fcis-2135	85	11	can	can	AUX
fcis-2135	85	12	perform	perform	VERB
fcis-2135	85	13	deep	deep	ADJ
fcis-2135	85	14	learning	learning	NOUN
fcis-2135	85	15	on	on	ADP
fcis-2135	85	16	graph	graph	NOUN
fcis-2135	85	17	data	datum	NOUN
fcis-2135	85	18	by	by	ADP
fcis-2135	85	19	using	use	VERB
fcis-2135	85	20	the	the	DET
fcis-2135	85	21	edge	edge	NOUN
fcis-2135	85	22	and	and	CCONJ
fcis-2135	85	23	node	node	ADJ
fcis-2135	85	24	data	datum	NOUN
fcis-2135	85	25	of	of	ADP
fcis-2135	85	26	the	the	DET
fcis-2135	85	27	graph	graph	NOUN
fcis-2135	85	28	as	as	ADP
fcis-2135	85	29	input	input	NOUN
fcis-2135	85	30	for	for	ADP
fcis-2135	85	31	learning	learning	NOUN
fcis-2135	85	32	and	and	CCONJ
fcis-2135	85	33	training	training	NOUN
fcis-2135	85	34	.	.	PUNCT
fcis-2135	86	1	although	although	SCONJ
fcis-2135	86	2	rnn	rnn	NOUN
fcis-2135	86	3	has	have	VERB
fcis-2135	86	4	significant	significant	ADJ
fcis-2135	86	5	sequence	sequence	NOUN
fcis-2135	86	6	modeling	modeling	NOUN
fcis-2135	86	7	ability	ability	NOUN
fcis-2135	86	8	,	,	PUNCT
fcis-2135	86	9	it	it	PRON
fcis-2135	86	10	lacks	lack	VERB
fcis-2135	86	11	intuitive	intuitive	ADJ
fcis-2135	86	12	high	high	ADJ
fcis-2135	86	13	-	-	PUNCT
fcis-2135	86	14	level	level	NOUN
fcis-2135	86	15	spatio	spatio	NOUN
fcis-2135	86	16	-	-	PUNCT
fcis-2135	86	17	temporal	temporal	ADJ
fcis-2135	86	18	structure	structure	NOUN
fcis-2135	86	19	.	.	PUNCT
fcis-2135	87	1	in	in	ADP
fcis-2135	87	2	the	the	DET
fcis-2135	87	3	field	field	NOUN
fcis-2135	87	4	of	of	ADP
fcis-2135	87	5	pedestrian	pedestrian	NOUN
fcis-2135	87	6	trajectory	trajectory	NOUN
fcis-2135	87	7	prediction	prediction	NOUN
fcis-2135	87	8	,	,	PUNCT
fcis-2135	87	9	the	the	DET
fcis-2135	87	10	number	number	NOUN
fcis-2135	87	11	of	of	ADP
fcis-2135	87	12	pedestrians	pedestrian	NOUN
fcis-2135	87	13	is	be	AUX
fcis-2135	87	14	uncertain	uncertain	ADJ
fcis-2135	87	15	,	,	PUNCT
fcis-2135	87	16	and	and	CCONJ
fcis-2135	87	17	the	the	DET
fcis-2135	87	18	interaction	interaction	NOUN
fcis-2135	87	19	between	between	ADP
fcis-2135	87	20	pedestrians	pedestrian	NOUN
fcis-2135	87	21	is	be	AUX
fcis-2135	87	22	irregular	irregular	ADJ
fcis-2135	87	23	.	.	PUNCT
fcis-2135	88	1	the	the	DET
fcis-2135	88	2	graph	graph	NOUN
fcis-2135	88	3	structure	structure	NOUN
fcis-2135	88	4	is	be	AUX
fcis-2135	88	5	a	a	DET
fcis-2135	88	6	natural	natural	ADJ
fcis-2135	88	7	method	method	NOUN
fcis-2135	88	8	to	to	PART
fcis-2135	88	9	represent	represent	VERB
fcis-2135	88	10	the	the	DET
fcis-2135	88	11	interaction	interaction	NOUN
fcis-2135	88	12	between	between	ADP
fcis-2135	88	13	pedestrians	pedestrian	NOUN
fcis-2135	88	14	.	.	PUNCT
fcis-2135	89	1	it	it	PRON
fcis-2135	89	2	is	be	AUX
fcis-2135	89	3	more	more	ADV
fcis-2135	89	4	intuitive	intuitive	ADJ
fcis-2135	89	5	and	and	CCONJ
fcis-2135	89	6	effective	effective	ADJ
fcis-2135	89	7	than	than	ADP
fcis-2135	89	8	the	the	DET
fcis-2135	89	9	rnn	rnn	NOUN
fcis-2135	89	10	method	method	NOUN
fcis-2135	89	11	based	base	VERB
fcis-2135	89	12	on	on	ADP
fcis-2135	89	13	aggregation	aggregation	NOUN
fcis-2135	89	14	.	.	PUNCT
fcis-2135	90	1	gcn	gcn	PROPN
fcis-2135	90	2	has	have	VERB
fcis-2135	90	3	a	a	DET
fcis-2135	90	4	great	great	ADJ
fcis-2135	90	5	effect	effect	NOUN
fcis-2135	90	6	on	on	ADP
fcis-2135	90	7	graph	graph	NOUN
fcis-2135	90	8	data	datum	NOUN
fcis-2135	90	9	processing	processing	NOUN
fcis-2135	90	10	in	in	ADP
fcis-2135	90	11	non	non	ADJ
fcis-2135	90	12	-	-	ADJ
fcis-2135	90	13	euclidean	euclidean	ADJ
fcis-2135	90	14	space	space	NOUN
fcis-2135	90	15	[	[	X
fcis-2135	90	16	23	23	NUM
fcis-2135	90	17	]	]	PUNCT
fcis-2135	90	18	.	.	PUNCT
fcis-2135	91	1	its	its	PRON
fcis-2135	91	2	core	core	ADJ
fcis-2135	91	3	idea	idea	NOUN
fcis-2135	91	4	is	be	AUX
fcis-2135	91	5	to	to	PART
fcis-2135	91	6	map	map	VERB
fcis-2135	91	7	nodes	node	NOUN
fcis-2135	91	8	or	or	CCONJ
fcis-2135	91	9	edges	edge	NOUN
fcis-2135	91	10	in	in	ADP
fcis-2135	91	11	graph	graph	NOUN
fcis-2135	91	12	structure	structure	NOUN
fcis-2135	91	13	to	to	ADP
fcis-2135	91	14	vector	vector	NOUN
fcis-2135	91	15	space	space	NOUN
fcis-2135	91	16	through	through	ADP
fcis-2135	91	17	deep	deep	ADJ
fcis-2135	91	18	learning	learning	NOUN
fcis-2135	91	19	methods	method	NOUN
fcis-2135	91	20	,	,	PUNCT
fcis-2135	91	21	and	and	CCONJ
fcis-2135	91	22	then	then	ADV
fcis-2135	91	23	perform	perform	VERB
fcis-2135	91	24	clustering	clustering	NOUN
fcis-2135	91	25	and	and	CCONJ
fcis-2135	91	26	classification	classification	NOUN
fcis-2135	91	27	.	.	PUNCT
fcis-2135	92	1	at	at	ADP
fcis-2135	92	2	present	present	ADJ
fcis-2135	92	3	,	,	PUNCT
fcis-2135	92	4	many	many	ADJ
fcis-2135	92	5	methods	method	NOUN
fcis-2135	92	6	[	[	PUNCT
fcis-2135	92	7	24	24	NUM
fcis-2135	92	8	-	-	SYM
fcis-2135	92	9	26	26	NUM
fcis-2135	92	10	]	]	PUNCT
fcis-2135	92	11	take	take	VERB
fcis-2135	92	12	graph	graph	NOUN
fcis-2135	92	13	structure	structure	NOUN
fcis-2135	92	14	as	as	ADP
fcis-2135	92	15	the	the	DET
fcis-2135	92	16	basic	basic	ADJ
fcis-2135	92	17	component	component	NOUN
fcis-2135	92	18	.	.	PUNCT
fcis-2135	93	1	these	these	DET
fcis-2135	93	2	methods	method	NOUN
fcis-2135	93	3	usually	usually	ADV
fcis-2135	93	4	represent	represent	VERB
fcis-2135	93	5	pedestrians	pedestrian	NOUN
fcis-2135	93	6	as	as	ADP
fcis-2135	93	7	nodes	node	NOUN
fcis-2135	93	8	,	,	PUNCT
fcis-2135	93	9	use	use	VERB
fcis-2135	93	10	their	their	PRON
fcis-2135	93	11	interactions	interaction	NOUN
fcis-2135	93	12	as	as	ADP
fcis-2135	93	13	connections	connection	NOUN
fcis-2135	93	14	,	,	PUNCT
fcis-2135	93	15	and	and	CCONJ
fcis-2135	93	16	combine	combine	VERB
fcis-2135	93	17	deep	deep	ADJ
fcis-2135	93	18	sequence	sequence	NOUN
fcis-2135	93	19	models	model	NOUN
fcis-2135	93	20	such	such	ADJ
fcis-2135	93	21	as	as	ADP
fcis-2135	93	22	long	long	ADJ
fcis-2135	93	23	short	short	ADJ
fcis-2135	93	24	-	-	PUNCT
fcis-2135	93	25	term	term	NOUN
fcis-2135	93	26	memory	memory	NOUN
fcis-2135	93	27	networks	network	NOUN
fcis-2135	93	28	for	for	ADP
fcis-2135	93	29	modeling	modeling	NOUN
fcis-2135	93	30	.	.	PUNCT
fcis-2135	94	1	[	[	X
fcis-2135	94	2	27	27	NUM
fcis-2135	94	3	]	]	PUNCT
fcis-2135	94	4	by	by	ADP
fcis-2135	94	5	adding	add	VERB
fcis-2135	94	6	spatiotemporal	spatiotemporal	ADJ
fcis-2135	94	7	data	datum	NOUN
fcis-2135	94	8	to	to	ADP
fcis-2135	94	9	pedestrian	pedestrian	NOUN
fcis-2135	94	10	trajectory	trajectory	NOUN
fcis-2135	94	11	prediction	prediction	NOUN
fcis-2135	94	12	,	,	PUNCT
fcis-2135	94	13	gcn	gcn	NOUN
fcis-2135	94	14	can	can	AUX
fcis-2135	94	15	understand	understand	VERB
fcis-2135	94	16	pedestrian	pedestrian	NOUN
fcis-2135	94	17	behavior	behavior	NOUN
fcis-2135	94	18	and	and	CCONJ
fcis-2135	94	19	accelerate	accelerate	VERB
fcis-2135	94	20	the	the	DET
fcis-2135	94	21	modeling	modeling	ADJ
fcis-2135	94	22	progress	progress	NOUN
fcis-2135	94	23	of	of	ADP
fcis-2135	94	24	social	social	ADJ
fcis-2135	94	25	interaction	interaction	NOUN
fcis-2135	94	26	.	.	PUNCT
fcis-2135	95	1	therefore	therefore	ADV
fcis-2135	95	2	,	,	PUNCT
fcis-2135	95	3	gcn	gcn	NOUN
fcis-2135	95	4	has	have	VERB
fcis-2135	95	5	great	great	ADJ
fcis-2135	95	6	application	application	NOUN
fcis-2135	95	7	prospects	prospect	NOUN
fcis-2135	95	8	in	in	ADP
fcis-2135	95	9	trajectory	trajectory	NOUN
fcis-2135	95	10	prediction	prediction	NOUN
fcis-2135	95	11	,	,	PUNCT
fcis-2135	95	12	but	but	CCONJ
fcis-2135	95	13	there	there	PRON
fcis-2135	95	14	are	be	VERB
fcis-2135	95	15	still	still	ADV
fcis-2135	95	16	some	some	DET
fcis-2135	95	17	problems	problem	NOUN
fcis-2135	95	18	such	such	ADJ
fcis-2135	95	19	as	as	ADP
fcis-2135	95	20	shallow	shallow	ADJ
fcis-2135	95	21	network	network	NOUN
fcis-2135	95	22	,	,	PUNCT
fcis-2135	95	23	unstable	unstable	ADJ
fcis-2135	95	24	structure	structure	NOUN
fcis-2135	95	25	and	and	CCONJ
fcis-2135	95	26	weak	weak	ADJ
fcis-2135	95	27	adaptive	adaptive	ADJ
fcis-2135	95	28	ability	ability	NOUN
fcis-2135	95	29	.	.	PUNCT
fcis-2135	96	1	pedestrian	pedestrian	NOUN
fcis-2135	96	2	trajectory	trajectory	NOUN
fcis-2135	96	3	prediction	prediction	NOUN
fcis-2135	96	4	based	base	VERB
fcis-2135	96	5	on	on	ADP
fcis-2135	96	6	gan	gan	PROPN
fcis-2135	96	7	.	.	PUNCT
fcis-2135	97	1	the	the	DET
fcis-2135	97	2	generative	generative	ADJ
fcis-2135	97	3	adversarial	adversarial	ADJ
fcis-2135	97	4	network	network	NOUN
fcis-2135	97	5	gan	gan	PROPN
fcis-2135	97	6	is	be	AUX
fcis-2135	97	7	a	a	DET
fcis-2135	97	8	deep	deep	ADJ
fcis-2135	97	9	learning	learning	NOUN
fcis-2135	97	10	model	model	NOUN
fcis-2135	97	11	of	of	ADP
fcis-2135	97	12	unsupervised	unsupervised	ADJ
fcis-2135	97	13	learning	learning	NOUN
fcis-2135	97	14	.	.	PUNCT
fcis-2135	98	1	the	the	DET
fcis-2135	98	2	gan	gan	PROPN
fcis-2135	98	3	network	network	NOUN
fcis-2135	98	4	overcomes	overcome	VERB
fcis-2135	98	5	the	the	DET
fcis-2135	98	6	difficulty	difficulty	NOUN
fcis-2135	98	7	of	of	ADP
fcis-2135	98	8	calculating	calculate	VERB
fcis-2135	98	9	the	the	DET
fcis-2135	98	10	generation	generation	NOUN
fcis-2135	98	11	probability	probability	NOUN
fcis-2135	98	12	by	by	ADP
fcis-2135	98	13	the	the	DET
fcis-2135	98	14	game	game	NOUN
fcis-2135	98	15	between	between	ADP
fcis-2135	98	16	the	the	DET
fcis-2135	98	17	generation	generation	NOUN
fcis-2135	98	18	model	model	NOUN
fcis-2135	98	19	and	and	CCONJ
fcis-2135	98	20	the	the	DET
fcis-2135	98	21	discriminant	discriminant	ADJ
fcis-2135	98	22	model	model	NOUN
fcis-2135	98	23	.	.	PUNCT
fcis-2135	99	1	adding	add	VERB
fcis-2135	99	2	gan	gan	PROPN
fcis-2135	99	3	network	network	NOUN
fcis-2135	99	4	to	to	ADP
fcis-2135	99	5	pedestrian	pedestrian	NOUN
fcis-2135	99	6	trajectory	trajectory	NOUN
fcis-2135	99	7	prediction	prediction	NOUN
fcis-2135	99	8	can	can	AUX
fcis-2135	99	9	solve	solve	VERB
fcis-2135	99	10	the	the	DET
fcis-2135	99	11	defect	defect	NOUN
fcis-2135	99	12	that	that	SCONJ
fcis-2135	99	13	only	only	ADV
fcis-2135	99	14	one	one	NUM
fcis-2135	99	15	'	'	PUNCT
fcis-2135	99	16	optimal	optimal	ADJ
fcis-2135	99	17	'	'	PUNCT
fcis-2135	99	18	trajectory	trajectory	NOUN
fcis-2135	99	19	can	can	AUX
fcis-2135	99	20	be	be	AUX
fcis-2135	99	21	predicted	predict	VERB
fcis-2135	99	22	in	in	ADP
fcis-2135	99	23	the	the	DET
fcis-2135	99	24	past	past	NOUN
fcis-2135	99	25	.	.	PUNCT
fcis-2135	100	1	the	the	DET
fcis-2135	100	2	network	network	NOUN
fcis-2135	100	3	can	can	AUX
fcis-2135	100	4	predict	predict	VERB
fcis-2135	100	5	multiple	multiple	ADJ
fcis-2135	100	6	feasible	feasible	ADJ
fcis-2135	100	7	trajectories	trajectory	NOUN
fcis-2135	100	8	and	and	CCONJ
fcis-2135	100	9	further	far	ADV
fcis-2135	100	10	optimize	optimize	VERB
fcis-2135	100	11	the	the	DET
fcis-2135	100	12	prediction	prediction	NOUN
fcis-2135	100	13	accuracy	accuracy	NOUN
fcis-2135	100	14	through	through	ADP
fcis-2135	100	15	game	game	NOUN
fcis-2135	100	16	theory	theory	NOUN
fcis-2135	100	17	.	.	PUNCT
fcis-2135	101	1	at	at	ADP
fcis-2135	101	2	the	the	DET
fcis-2135	101	3	same	same	ADJ
fcis-2135	101	4	time	time	NOUN
fcis-2135	101	5	,	,	PUNCT
fcis-2135	101	6	drawing	draw	VERB
fcis-2135	101	7	on	on	ADP
fcis-2135	101	8	the	the	DET
fcis-2135	101	9	successful	successful	ADJ
fcis-2135	101	10	experience	experience	NOUN
fcis-2135	101	11	of	of	ADP
fcis-2135	101	12	gan	gan	ADJ
fcis-2135	101	13	network	network	NOUN
fcis-2135	101	14	in	in	ADP
fcis-2135	101	15	the	the	DET
fcis-2135	101	16	fields	field	NOUN
fcis-2135	101	17	of	of	ADP
fcis-2135	101	18	super	super	NOUN
fcis-2135	101	19	-	-	NOUN
fcis-2135	101	20	resolution	resolution	NOUN
fcis-2135	101	21	,	,	PUNCT
fcis-2135	101	22	image	image	NOUN
fcis-2135	101	23	conversion	conversion	NOUN
fcis-2135	101	24	and	and	CCONJ
fcis-2135	101	25	image	image	NOUN
fcis-2135	101	26	synthesis	synthesis	NOUN
fcis-2135	101	27	,	,	PUNCT
fcis-2135	101	28	the	the	DET
fcis-2135	101	29	trajectory	trajectory	NOUN
fcis-2135	101	30	sampler	sampler	NOUN
fcis-2135	102	1	[	[	X
fcis-2135	102	2	28	28	NUM
fcis-2135	102	3	]	]	PUNCT
fcis-2135	102	4	combines	combine	VERB
fcis-2135	102	5	the	the	DET
fcis-2135	102	6	gan	gan	PROPN
fcis-2135	102	7	input	input	NOUN
fcis-2135	102	8	random	random	ADJ
fcis-2135	102	9	vector	vector	NOUN
fcis-2135	102	10	with	with	ADP
fcis-2135	102	11	the	the	DET
fcis-2135	102	12	hidden	hide	VERB
fcis-2135	102	13	representation	representation	NOUN
fcis-2135	102	14	of	of	ADP
fcis-2135	102	15	other	other	ADJ
fcis-2135	102	16	pedestrian	pedestrian	NOUN
fcis-2135	102	17	trajectories	trajectory	NOUN
fcis-2135	102	18	to	to	PART
fcis-2135	102	19	deal	deal	VERB
fcis-2135	102	20	with	with	ADP
fcis-2135	102	21	the	the	DET
fcis-2135	102	22	interaction	interaction	NOUN
fcis-2135	102	23	between	between	ADP
fcis-2135	102	24	all	all	DET
fcis-2135	102	25	observed	observed	ADJ
fcis-2135	102	26	pedestrians	pedestrian	NOUN
fcis-2135	102	27	.	.	PUNCT
fcis-2135	103	1	however	however	ADV
fcis-2135	103	2	,	,	PUNCT
fcis-2135	103	3	the	the	DET
fcis-2135	103	4	neural	neural	ADJ
fcis-2135	103	5	network	network	NOUN
fcis-2135	103	6	based	base	VERB
fcis-2135	103	7	on	on	ADP
fcis-2135	103	8	gan	gan	PROPN
fcis-2135	103	9	model	model	NOUN
fcis-2135	103	10	is	be	AUX
fcis-2135	103	11	prone	prone	ADJ
fcis-2135	103	12	to	to	ADP
fcis-2135	103	13	problems	problem	NOUN
fcis-2135	103	14	such	such	ADJ
fcis-2135	103	15	as	as	ADP
fcis-2135	103	16	slow	slow	ADJ
fcis-2135	103	17	convergence	convergence	NOUN
fcis-2135	103	18	and	and	CCONJ
fcis-2135	103	19	mode	mode	NOUN
fcis-2135	103	20	collapse	collapse	NOUN
fcis-2135	103	21	.	.	PUNCT
fcis-2135	104	1	3	3	X
fcis-2135	104	2	.	.	X
fcis-2135	104	3	comparison	comparison	NOUN
fcis-2135	104	4	of	of	ADP
fcis-2135	104	5	pedestrian	pedestrian	NOUN
fcis-2135	104	6	trajectory	trajectory	NOUN
fcis-2135	104	7	prediction	prediction	NOUN
fcis-2135	104	8	methods	method	NOUN
fcis-2135	104	9	since	since	SCONJ
fcis-2135	104	10	the	the	DET
fcis-2135	104	11	1990s	1990s	NUM
fcis-2135	104	12	,	,	PUNCT
fcis-2135	104	13	a	a	DET
fcis-2135	104	14	large	large	ADJ
fcis-2135	104	15	number	number	NOUN
fcis-2135	104	16	of	of	ADP
fcis-2135	104	17	trajectory	trajectory	NOUN
fcis-2135	104	18	prediction	prediction	NOUN
fcis-2135	104	19	networks	network	NOUN
fcis-2135	104	20	based	base	VERB
fcis-2135	104	21	on	on	ADP
fcis-2135	104	22	shallow	shallow	ADJ
fcis-2135	104	23	learning	learning	NOUN
fcis-2135	104	24	have	have	AUX
fcis-2135	104	25	been	be	AUX
fcis-2135	104	26	proposed	propose	VERB
fcis-2135	104	27	.	.	PUNCT
fcis-2135	105	1	these	these	DET
fcis-2135	105	2	models	model	NOUN
fcis-2135	105	3	have	have	VERB
fcis-2135	105	4	high	high	ADJ
fcis-2135	105	5	requirements	requirement	NOUN
fcis-2135	105	6	on	on	ADP
fcis-2135	105	7	the	the	DET
fcis-2135	105	8	calculation	calculation	NOUN
fcis-2135	105	9	examples	example	NOUN
fcis-2135	105	10	of	of	ADP
fcis-2135	105	11	computing	compute	VERB
fcis-2135	105	12	equipment	equipment	NOUN
fcis-2135	105	13	,	,	PUNCT
fcis-2135	105	14	and	and	CCONJ
fcis-2135	105	15	lack	lack	VERB
fcis-2135	105	16	unified	unified	ADJ
fcis-2135	105	17	evaluation	evaluation	NOUN
fcis-2135	105	18	criteria	criterion	NOUN
fcis-2135	105	19	.	.	PUNCT
fcis-2135	106	1	the	the	DET
fcis-2135	106	2	quality	quality	NOUN
fcis-2135	106	3	of	of	ADP
fcis-2135	106	4	the	the	DET
fcis-2135	106	5	data	data	NOUN
fcis-2135	106	6	sets	set	NOUN
fcis-2135	106	7	used	use	VERB
fcis-2135	106	8	to	to	PART
fcis-2135	106	9	test	test	VERB
fcis-2135	106	10	the	the	DET
fcis-2135	106	11	model	model	NOUN
fcis-2135	106	12	is	be	AUX
fcis-2135	106	13	also	also	ADV
fcis-2135	106	14	uneven	uneven	ADJ
fcis-2135	106	15	.	.	PUNCT
fcis-2135	107	1	therefore	therefore	ADV
fcis-2135	107	2	,	,	PUNCT
fcis-2135	107	3	there	there	PRON
fcis-2135	107	4	is	be	VERB
fcis-2135	107	5	little	little	ADJ
fcis-2135	107	6	review	review	NOUN
fcis-2135	107	7	of	of	ADP
fcis-2135	107	8	trajectory	trajectory	NOUN
fcis-2135	107	9	prediction	prediction	NOUN
fcis-2135	107	10	models	model	NOUN
fcis-2135	107	11	based	base	VERB
fcis-2135	107	12	on	on	ADP
fcis-2135	107	13	shallow	shallow	ADJ
fcis-2135	107	14	learning	learning	NOUN
fcis-2135	107	15	.	.	PUNCT
fcis-2135	108	1	in	in	ADP
fcis-2135	108	2	recent	recent	ADJ
fcis-2135	108	3	years	year	NOUN
fcis-2135	108	4	,	,	PUNCT
fcis-2135	108	5	machine	machine	NOUN
fcis-2135	108	6	learning	learning	NOUN
fcis-2135	108	7	technology	technology	NOUN
fcis-2135	108	8	,	,	PUNCT
fcis-2135	108	9	especially	especially	ADV
fcis-2135	108	10	deep	deep	ADJ
fcis-2135	108	11	learning	learning	NOUN
fcis-2135	108	12	technology	technology	NOUN
fcis-2135	108	13	,	,	PUNCT
fcis-2135	108	14	has	have	AUX
fcis-2135	108	15	gradually	gradually	ADV
fcis-2135	108	16	emerged	emerge	VERB
fcis-2135	108	17	.	.	PUNCT
fcis-2135	109	1	due	due	ADP
fcis-2135	109	2	to	to	ADP
fcis-2135	109	3	the	the	DET
fcis-2135	109	4	excellent	excellent	ADJ
fcis-2135	109	5	performance	performance	NOUN
fcis-2135	109	6	of	of	ADP
fcis-2135	109	7	recurrent	recurrent	ADJ
fcis-2135	109	8	neural	neural	ADJ
fcis-2135	109	9	network	network	NOUN
fcis-2135	109	10	in	in	ADP
fcis-2135	109	11	processing	processing	NOUN
fcis-2135	109	12	time	time	NOUN
fcis-2135	109	13	series	series	PROPN
fcis-2135	109	14	data	data	PROPN
fcis-2135	109	15	,	,	PUNCT
fcis-2135	109	16	time	time	NOUN
fcis-2135	109	17	series	series	PROPN
fcis-2135	109	18	prediction	prediction	NOUN
fcis-2135	109	19	models	model	NOUN
fcis-2135	109	20	based	base	VERB
fcis-2135	109	21	on	on	ADP
fcis-2135	109	22	recurrent	recurrent	ADJ
fcis-2135	109	23	neural	neural	ADJ
fcis-2135	109	24	network	network	NOUN
fcis-2135	109	25	emerge	emerge	VERB
fcis-2135	109	26	in	in	ADP
fcis-2135	109	27	endlessly	endlessly	ADV
fcis-2135	109	28	.	.	PUNCT
fcis-2135	110	1	the	the	DET
fcis-2135	110	2	following	follow	VERB
fcis-2135	110	3	will	will	AUX
fcis-2135	110	4	classify	classify	VERB
fcis-2135	110	5	and	and	CCONJ
fcis-2135	110	6	summarize	summarize	VERB
fcis-2135	110	7	the	the	DET
fcis-2135	110	8	main	main	ADJ
fcis-2135	110	9	pedestrian	pedestrian	NOUN
fcis-2135	110	10	trajectory	trajectory	NOUN
fcis-2135	110	11	prediction	prediction	NOUN
fcis-2135	110	12	methods	method	NOUN
fcis-2135	110	13	at	at	ADP
fcis-2135	110	14	home	home	NOUN
fcis-2135	110	15	and	and	CCONJ
fcis-2135	110	16	abroad	abroad	ADV
fcis-2135	110	17	.	.	PUNCT
fcis-2135	111	1	according	accord	VERB
fcis-2135	111	2	to	to	ADP
fcis-2135	111	3	the	the	DET
fcis-2135	111	4	modeling	modeling	NOUN
fcis-2135	111	5	method	method	NOUN
fcis-2135	111	6	of	of	ADP
fcis-2135	111	7	the	the	DET
fcis-2135	111	8	prediction	prediction	NOUN
fcis-2135	111	9	model	model	NOUN
fcis-2135	111	10	,	,	PUNCT
fcis-2135	111	11	pedestrian	pedestrian	NOUN
fcis-2135	111	12	trajectory	trajectory	NOUN
fcis-2135	111	13	prediction	prediction	NOUN
fcis-2135	111	14	methods	method	NOUN
fcis-2135	111	15	are	be	AUX
fcis-2135	111	16	roughly	roughly	ADV
fcis-2135	111	17	divided	divide	VERB
fcis-2135	111	18	into	into	ADP
fcis-2135	111	19	trajectory	trajectory	NOUN
fcis-2135	111	20	prediction	prediction	NOUN
fcis-2135	111	21	methods	method	NOUN
fcis-2135	111	22	based	base	VERB
fcis-2135	111	23	on	on	ADP
fcis-2135	111	24	shallow	shallow	ADJ
fcis-2135	111	25	learning	learning	NOUN
fcis-2135	111	26	and	and	CCONJ
fcis-2135	111	27	trajectory	trajectory	NOUN
fcis-2135	111	28	prediction	prediction	NOUN
fcis-2135	111	29	methods	method	NOUN
fcis-2135	111	30	based	base	VERB
fcis-2135	111	31	on	on	ADP
fcis-2135	111	32	deep	deep	ADJ
fcis-2135	111	33	learning	learning	NOUN
fcis-2135	111	34	.	.	PUNCT
fcis-2135	112	1	among	among	ADP
fcis-2135	112	2	them	they	PRON
fcis-2135	112	3	,	,	PUNCT
fcis-2135	112	4	the	the	DET
fcis-2135	112	5	kinematics	kinematics	NOUN
fcis-2135	112	6	-	-	PUNCT
fcis-2135	112	7	based	base	VERB
fcis-2135	112	8	method	method	NOUN
fcis-2135	112	9	in	in	ADP
fcis-2135	112	10	shallow	shallow	ADJ
fcis-2135	112	11	learning	learning	NOUN
fcis-2135	112	12	is	be	AUX
fcis-2135	112	13	the	the	DET
fcis-2135	112	14	first	first	ADJ
fcis-2135	112	15	to	to	PART
fcis-2135	112	16	be	be	AUX
fcis-2135	112	17	applied	apply	VERB
fcis-2135	112	18	in	in	ADP
fcis-2135	112	19	the	the	DET
fcis-2135	112	20	field	field	NOUN
fcis-2135	112	21	of	of	ADP
fcis-2135	112	22	trajectory	trajectory	NOUN
fcis-2135	112	23	prediction	prediction	NOUN
fcis-2135	112	24	.	.	PUNCT
fcis-2135	113	1	such	such	ADJ
fcis-2135	113	2	methods	method	NOUN
fcis-2135	113	3	generally	generally	ADV
fcis-2135	113	4	need	need	VERB
fcis-2135	113	5	to	to	PART
fcis-2135	113	6	model	model	VERB
fcis-2135	113	7	the	the	DET
fcis-2135	113	8	kinematic	kinematic	ADJ
fcis-2135	113	9	characteristics	characteristic	NOUN
fcis-2135	113	10	(	(	PUNCT
fcis-2135	113	11	speed	speed	NOUN
fcis-2135	113	12	,	,	PUNCT
fcis-2135	113	13	position	position	NOUN
fcis-2135	113	14	and	and	CCONJ
fcis-2135	113	15	angular	angular	ADJ
fcis-2135	113	16	velocity	velocity	NOUN
fcis-2135	113	17	,	,	PUNCT
fcis-2135	113	18	etc	etc	X
fcis-2135	113	19	.	.	X
fcis-2135	113	20	)	)	PUNCT
fcis-2135	113	21	of	of	ADP
fcis-2135	113	22	pedestrians	pedestrian	NOUN
fcis-2135	113	23	and	and	CCONJ
fcis-2135	113	24	combine	combine	VERB
fcis-2135	113	25	them	they	PRON
fcis-2135	113	26	with	with	ADP
fcis-2135	113	27	bayesian	bayesian	NOUN
fcis-2135	113	28	filters	filter	NOUN
fcis-2135	113	29	,	,	PUNCT
fcis-2135	113	30	markov	markov	NOUN
fcis-2135	113	31	networks	network	NOUN
fcis-2135	113	32	or	or	CCONJ
fcis-2135	113	33	bayesian	bayesian	NOUN
fcis-2135	113	34	networks	network	NOUN
fcis-2135	113	35	to	to	PART
fcis-2135	113	36	propagate	propagate	VERB
fcis-2135	113	37	the	the	DET
fcis-2135	113	38	current	current	ADJ
fcis-2135	113	39	state	state	NOUN
fcis-2135	113	40	to	to	ADP
fcis-2135	113	41	the	the	DET
fcis-2135	113	42	future	future	ADJ
fcis-2135	113	43	state	state	NOUN
fcis-2135	113	44	for	for	ADP
fcis-2135	113	45	prediction	prediction	NOUN
fcis-2135	113	46	.	.	PUNCT
fcis-2135	114	1	according	accord	VERB
fcis-2135	114	2	to	to	ADP
fcis-2135	114	3	whether	whether	SCONJ
fcis-2135	114	4	the	the	DET
fcis-2135	114	5	interaction	interaction	NOUN
fcis-2135	114	6	between	between	ADP
fcis-2135	114	7	pedestrians	pedestrian	NOUN
fcis-2135	114	8	is	be	AUX
fcis-2135	114	9	considered	consider	VERB
fcis-2135	114	10	,	,	PUNCT
fcis-2135	114	11	the	the	DET
fcis-2135	114	12	trajectory	trajectory	NOUN
fcis-2135	114	13	prediction	prediction	NOUN
fcis-2135	114	14	model	model	NOUN
fcis-2135	114	15	based	base	VERB
fcis-2135	114	16	on	on	ADP
fcis-2135	114	17	deep	deep	ADJ
fcis-2135	114	18	learning	learning	NOUN
fcis-2135	114	19	can	can	AUX
fcis-2135	114	20	be	be	AUX
fcis-2135	114	21	divided	divide	VERB
fcis-2135	114	22	into	into	ADP
fcis-2135	114	23	single	single	ADJ
fcis-2135	114	24	trajectory	trajectory	NOUN
fcis-2135	114	25	prediction	prediction	NOUN
fcis-2135	114	26	model	model	NOUN
fcis-2135	114	27	and	and	CCONJ
fcis-2135	114	28	interactive	interactive	ADJ
fcis-2135	114	29	trajectory	trajectory	NOUN
fcis-2135	114	30	prediction	prediction	NOUN
fcis-2135	114	31	model	model	NOUN
fcis-2135	114	32	.	.	PUNCT
fcis-2135	115	1	according	accord	VERB
fcis-2135	115	2	to	to	ADP
fcis-2135	115	3	whether	whether	SCONJ
fcis-2135	115	4	to	to	PART
fcis-2135	115	5	generate	generate	VERB
fcis-2135	115	6	deterministic	deterministic	ADJ
fcis-2135	115	7	pedestrian	pedestrian	NOUN
fcis-2135	115	8	trajectory	trajectory	NOUN
fcis-2135	115	9	,	,	PUNCT
fcis-2135	115	10	it	it	PRON
fcis-2135	115	11	can	can	AUX
fcis-2135	115	12	be	be	AUX
fcis-2135	115	13	divided	divide	VERB
fcis-2135	115	14	into	into	ADP
fcis-2135	115	15	deterministic	deterministic	ADJ
fcis-2135	115	16	trajectory	trajectory	NOUN
fcis-2135	115	17	prediction	prediction	NOUN
fcis-2135	115	18	model	model	NOUN
fcis-2135	115	19	and	and	CCONJ
fcis-2135	115	20	acceptable	acceptable	ADJ
fcis-2135	115	21	trajectory	trajectory	NOUN
fcis-2135	115	22	prediction	prediction	NOUN
fcis-2135	115	23	model	model	NOUN
fcis-2135	115	24	.	.	PUNCT
fcis-2135	116	1	with	with	ADP
fcis-2135	116	2	the	the	DET
fcis-2135	116	3	introduction	introduction	NOUN
fcis-2135	116	4	and	and	CCONJ
fcis-2135	116	5	optimization	optimization	NOUN
fcis-2135	116	6	of	of	ADP
fcis-2135	116	7	the	the	DET
fcis-2135	116	8	model	model	NOUN
fcis-2135	116	9	,	,	PUNCT
fcis-2135	116	10	the	the	DET
fcis-2135	116	11	current	current	ADJ
fcis-2135	116	12	trajectory	trajectory	NOUN
fcis-2135	116	13	prediction	prediction	NOUN
fcis-2135	116	14	method	method	NOUN
fcis-2135	116	15	based	base	VERB
fcis-2135	116	16	on	on	ADP
fcis-2135	116	17	deep	deep	ADJ
fcis-2135	116	18	learning	learning	NOUN
fcis-2135	116	19	tends	tend	VERB
fcis-2135	116	20	to	to	PART
fcis-2135	116	21	be	be	AUX
fcis-2135	116	22	modular	modular	ADJ
fcis-2135	116	23	,	,	PUNCT
fcis-2135	116	24	the	the	DET
fcis-2135	116	25	information	information	NOUN
fcis-2135	116	26	that	that	PRON
fcis-2135	116	27	needs	need	VERB
fcis-2135	116	28	to	to	PART
fcis-2135	116	29	be	be	AUX
fcis-2135	116	30	considered	consider	VERB
fcis-2135	116	31	and	and	CCONJ
fcis-2135	116	32	utilized	utilize	VERB
fcis-2135	116	33	is	be	AUX
fcis-2135	116	34	gradually	gradually	ADV
fcis-2135	116	35	improved	improve	VERB
fcis-2135	116	36	,	,	PUNCT
fcis-2135	116	37	and	and	CCONJ
fcis-2135	116	38	the	the	DET
fcis-2135	116	39	accuracy	accuracy	NOUN
fcis-2135	116	40	and	and	CCONJ
fcis-2135	116	41	real	real	ADJ
fcis-2135	116	42	-	-	PUNCT
fcis-2135	116	43	time	time	NOUN
fcis-2135	116	44	performance	performance	NOUN
fcis-2135	116	45	of	of	ADP
fcis-2135	116	46	the	the	DET
fcis-2135	116	47	prediction	prediction	NOUN
fcis-2135	116	48	are	be	AUX
fcis-2135	116	49	gradually	gradually	ADV
fcis-2135	116	50	improved	improve	VERB
fcis-2135	116	51	.	.	PUNCT
fcis-2135	117	1	the	the	DET
fcis-2135	117	2	classification	classification	NOUN
fcis-2135	117	3	of	of	ADP
fcis-2135	117	4	pedestrian	pedestrian	NOUN
fcis-2135	117	5	trajectory	trajectory	NOUN
fcis-2135	117	6	prediction	prediction	NOUN
fcis-2135	117	7	methods	method	NOUN
fcis-2135	117	8	is	be	AUX
fcis-2135	117	9	shown	show	VERB
fcis-2135	117	10	in	in	ADP
fcis-2135	117	11	figure	figure	NOUN
fcis-2135	117	12	2	2	NUM
fcis-2135	117	13	.	.	PUNCT
fcis-2135	117	14	fig	fig	NOUN
fcis-2135	117	15	.	.	PUNCT
fcis-2135	118	1	2	2	NUM
fcis-2135	118	2	classification	classification	NOUN
fcis-2135	118	3	of	of	ADP
fcis-2135	118	4	pedestrian	pedestrian	NOUN
fcis-2135	118	5	trajectory	trajectory	NOUN
fcis-2135	118	6	prediction	prediction	NOUN
fcis-2135	118	7	methods	method	NOUN
fcis-2135	118	8	3.1	3.1	NUM
fcis-2135	118	9	.	.	PUNCT
fcis-2135	118	10	trajectory	trajectory	NOUN
fcis-2135	118	11	prediction	prediction	NOUN
fcis-2135	118	12	method	method	NOUN
fcis-2135	118	13	based	base	VERB
fcis-2135	118	14	on	on	ADP
fcis-2135	118	15	shallow	shallow	ADJ
fcis-2135	118	16	learning	learn	VERB
fcis-2135	118	17	the	the	DET
fcis-2135	118	18	initial	initial	ADJ
fcis-2135	118	19	trajectory	trajectory	NOUN
fcis-2135	118	20	prediction	prediction	NOUN
fcis-2135	118	21	method	method	NOUN
fcis-2135	118	22	was	be	AUX
fcis-2135	118	23	to	to	PART
fcis-2135	118	24	combine	combine	VERB
fcis-2135	118	25	the	the	DET
fcis-2135	118	26	basic	basic	ADJ
fcis-2135	118	27	kinematic	kinematic	ADJ
fcis-2135	118	28	model	model	NOUN
fcis-2135	118	29	with	with	ADP
fcis-2135	118	30	the	the	DET
fcis-2135	118	31	bayesian	bayesian	NOUN
fcis-2135	118	32	filter	filter	NOUN
fcis-2135	118	33	and	and	CCONJ
fcis-2135	118	34	its	its	PRON
fcis-2135	118	35	extensions	extension	NOUN
fcis-2135	118	36	to	to	PART
fcis-2135	118	37	propagate	propagate	VERB
fcis-2135	118	38	the	the	DET
fcis-2135	118	39	current	current	ADJ
fcis-2135	118	40	state	state	NOUN
fcis-2135	118	41	to	to	ADP
fcis-2135	118	42	the	the	DET
fcis-2135	118	43	future	future	ADJ
fcis-2135	118	44	state	state	NOUN
fcis-2135	118	45	[	[	X
fcis-2135	118	46	29	29	NUM
fcis-2135	118	47	]	]	PUNCT
fcis-2135	118	48	.	.	PUNCT
fcis-2135	119	1	schneider	schneider	PROPN
fcis-2135	119	2	et	et	PROPN
fcis-2135	119	3	al	al	PROPN
fcis-2135	119	4	.	.	PUNCT
fcis-2135	120	1	[	[	X
fcis-2135	120	2	30	30	NUM
fcis-2135	120	3	]	]	PUNCT
fcis-2135	120	4	compared	compare	VERB
fcis-2135	120	5	the	the	DET
fcis-2135	120	6	method	method	NOUN
fcis-2135	120	7	based	base	VERB
fcis-2135	120	8	on	on	ADP
fcis-2135	120	9	a	a	DET
fcis-2135	120	10	single	single	ADJ
fcis-2135	120	11	kinematic	kinematic	ADJ
fcis-2135	120	12	model	model	NOUN
fcis-2135	120	13	with	with	ADP
fcis-2135	120	14	the	the	DET
fcis-2135	120	15	method	method	NOUN
fcis-2135	120	16	based	base	VERB
fcis-2135	120	17	on	on	ADP
fcis-2135	120	18	multimodel	multimodel	PROPN
fcis-2135	120	19	interaction	interaction	NOUN
fcis-2135	120	20	.	.	PUNCT
fcis-2135	121	1	the	the	DET
fcis-2135	121	2	results	result	NOUN
fcis-2135	121	3	show	show	VERB
fcis-2135	121	4	that	that	SCONJ
fcis-2135	121	5	the	the	DET
fcis-2135	121	6	method	method	NOUN
fcis-2135	121	7	based	base	VERB
fcis-2135	121	8	on	on	ADP
fcis-2135	121	9	multi	multi	ADJ
fcis-2135	121	10	-	-	ADJ
fcis-2135	121	11	model	model	ADJ
fcis-2135	121	12	interaction	interaction	NOUN
fcis-2135	121	13	can	can	AUX
fcis-2135	121	14	reduce	reduce	VERB
fcis-2135	121	15	the	the	DET
fcis-2135	121	16	lateral	lateral	ADJ
fcis-2135	121	17	position	position	NOUN
fcis-2135	121	18	estimation	estimation	NOUN
fcis-2135	121	19	error	error	NOUN
fcis-2135	121	20	of	of	ADP
fcis-2135	121	21	30	30	NUM
fcis-2135	121	22	cm	cm	NOUN
fcis-2135	121	23	during	during	ADP
fcis-2135	121	24	maneuvering	maneuver	VERB
fcis-2135	121	25	.	.	PUNCT
fcis-2135	122	1	however	however	ADV
fcis-2135	122	2	,	,	PUNCT
fcis-2135	122	3	because	because	SCONJ
fcis-2135	122	4	the	the	DET
fcis-2135	122	5	model	model	NOUN
fcis-2135	122	6	assumes	assume	VERB
fcis-2135	122	7	of	of	ADP
fcis-2135	122	8	constant	constant	ADJ
fcis-2135	122	9	speed	speed	NOUN
fcis-2135	122	10	,	,	PUNCT
fcis-2135	122	11	it	it	PRON
fcis-2135	122	12	also	also	ADV
fcis-2135	122	13	makes	make	VERB
fcis-2135	122	14	it	it	PRON
fcis-2135	122	15	difficult	difficult	ADJ
fcis-2135	122	16	for	for	SCONJ
fcis-2135	122	17	the	the	DET
fcis-2135	122	18	model	model	NOUN
fcis-2135	122	19	based	base	VERB
fcis-2135	122	20	on	on	ADP
fcis-2135	122	21	bayesian	bayesian	NOUN
fcis-2135	122	22	filter	filter	NOUN
fcis-2135	122	23	to	to	PART
fcis-2135	122	24	capture	capture	VERB
fcis-2135	122	25	the	the	DET
fcis-2135	122	26	71	71	NUM
fcis-2135	122	27	switching	switching	NOUN
fcis-2135	122	28	dynamics	dynamic	NOUN
fcis-2135	122	29	of	of	ADP
fcis-2135	122	30	pedestrians	pedestrian	NOUN
fcis-2135	122	31	,	,	PUNCT
fcis-2135	122	32	and	and	CCONJ
fcis-2135	122	33	the	the	DET
fcis-2135	122	34	number	number	NOUN
fcis-2135	122	35	of	of	ADP
fcis-2135	122	36	data	datum	NOUN
fcis-2135	122	37	sets	set	NOUN
fcis-2135	122	38	and	and	CCONJ
fcis-2135	122	39	motion	motion	NOUN
fcis-2135	122	40	types	type	NOUN
fcis-2135	122	41	used	use	VERB
fcis-2135	122	42	for	for	ADP
fcis-2135	122	43	testing	testing	NOUN
fcis-2135	122	44	are	be	AUX
fcis-2135	122	45	limited	limit	VERB
fcis-2135	122	46	,	,	PUNCT
fcis-2135	122	47	which	which	PRON
fcis-2135	122	48	is	be	AUX
fcis-2135	122	49	not	not	PART
fcis-2135	122	50	enough	enough	ADJ
fcis-2135	122	51	to	to	PART
fcis-2135	122	52	support	support	VERB
fcis-2135	122	53	the	the	DET
fcis-2135	122	54	establishment	establishment	NOUN
fcis-2135	122	55	and	and	CCONJ
fcis-2135	122	56	prediction	prediction	NOUN
fcis-2135	122	57	of	of	ADP
fcis-2135	122	58	more	more	ADJ
fcis-2135	122	59	complex	complex	ADJ
fcis-2135	122	60	motion	motion	NOUN
fcis-2135	122	61	models	model	NOUN
fcis-2135	122	62	.	.	PUNCT
fcis-2135	123	1	pavlovic	pavlovic	ADV
fcis-2135	123	2	et	et	PROPN
fcis-2135	123	3	al	al	PROPN
fcis-2135	123	4	.	.	PUNCT
fcis-2135	124	1	[	[	X
fcis-2135	124	2	31	31	NUM
fcis-2135	124	3	]	]	PUNCT
fcis-2135	124	4	used	use	VERB
fcis-2135	124	5	the	the	DET
fcis-2135	124	6	switched	switch	VERB
fcis-2135	124	7	linear	linear	ADJ
fcis-2135	124	8	dynamic	dynamic	ADJ
fcis-2135	124	9	system	system	NOUN
fcis-2135	124	10	(	(	PUNCT
fcis-2135	124	11	slds	slds	PROPN
fcis-2135	124	12	)	)	PUNCT
fcis-2135	124	13	model	model	NOUN
fcis-2135	124	14	[	[	X
fcis-2135	124	15	32	32	NUM
fcis-2135	124	16	]	]	PUNCT
fcis-2135	124	17	to	to	PART
fcis-2135	124	18	describe	describe	VERB
fcis-2135	124	19	nonlinear	nonlinear	ADJ
fcis-2135	124	20	and	and	CCONJ
fcis-2135	124	21	time	time	NOUN
fcis-2135	124	22	-	-	PUNCT
fcis-2135	124	23	varying	vary	VERB
fcis-2135	124	24	dynamics	dynamic	NOUN
fcis-2135	124	25	.	.	PUNCT
fcis-2135	125	1	the	the	DET
fcis-2135	125	2	model	model	NOUN
fcis-2135	125	3	is	be	AUX
fcis-2135	125	4	based	base	VERB
fcis-2135	125	5	on	on	ADP
fcis-2135	125	6	a	a	DET
fcis-2135	125	7	markov	markov	NOUN
fcis-2135	125	8	chain	chain	NOUN
fcis-2135	125	9	for	for	ADP
fcis-2135	125	10	probability	probability	NOUN
fcis-2135	125	11	transfer	transfer	NOUN
fcis-2135	125	12	,	,	PUNCT
fcis-2135	125	13	and	and	CCONJ
fcis-2135	125	14	switches	switch	NOUN
fcis-2135	125	15	between	between	ADP
fcis-2135	125	16	multiple	multiple	ADJ
fcis-2135	125	17	linear	linear	ADJ
fcis-2135	125	18	kinematic	kinematic	NOUN
fcis-2135	125	19	models	model	NOUN
fcis-2135	125	20	to	to	PART
fcis-2135	125	21	predict	predict	VERB
fcis-2135	125	22	nonlinear	nonlinear	ADJ
fcis-2135	125	23	motion	motion	NOUN
fcis-2135	125	24	in	in	ADP
fcis-2135	125	25	the	the	DET
fcis-2135	125	26	actual	actual	ADJ
fcis-2135	125	27	situation	situation	NOUN
fcis-2135	125	28	.	.	PUNCT
fcis-2135	126	1	however	however	ADV
fcis-2135	126	2	,	,	PUNCT
fcis-2135	126	3	the	the	DET
fcis-2135	126	4	motion	motion	NOUN
fcis-2135	126	5	feature	feature	NOUN
fcis-2135	126	6	information	information	NOUN
fcis-2135	126	7	based	base	VERB
fcis-2135	126	8	on	on	ADP
fcis-2135	126	9	this	this	DET
fcis-2135	126	10	model	model	NOUN
fcis-2135	126	11	is	be	AUX
fcis-2135	126	12	sometimes	sometimes	ADV
fcis-2135	126	13	insufficient	insufficient	ADJ
fcis-2135	126	14	to	to	PART
fcis-2135	126	15	support	support	VERB
fcis-2135	126	16	the	the	DET
fcis-2135	126	17	model	model	NOUN
fcis-2135	126	18	to	to	PART
fcis-2135	126	19	switch	switch	VERB
fcis-2135	126	20	states	state	NOUN
fcis-2135	126	21	,	,	PUNCT
fcis-2135	126	22	and	and	CCONJ
fcis-2135	126	23	its	its	PRON
fcis-2135	126	24	effect	effect	NOUN
fcis-2135	126	25	is	be	AUX
fcis-2135	126	26	limited	limit	VERB
fcis-2135	126	27	for	for	ADP
fcis-2135	126	28	some	some	DET
fcis-2135	126	29	more	more	ADV
fcis-2135	126	30	complex	complex	ADJ
fcis-2135	126	31	motion	motion	NOUN
fcis-2135	126	32	models	model	NOUN
fcis-2135	126	33	.	.	PUNCT
fcis-2135	127	1	it	it	PRON
fcis-2135	127	2	is	be	AUX
fcis-2135	127	3	necessary	necessary	ADJ
fcis-2135	127	4	to	to	PART
fcis-2135	127	5	build	build	VERB
fcis-2135	127	6	larger	large	ADJ
fcis-2135	127	7	motion	motion	NOUN
fcis-2135	127	8	capture	capture	NOUN
fcis-2135	127	9	data	datum	NOUN
fcis-2135	127	10	sets	set	NOUN
fcis-2135	127	11	to	to	PART
fcis-2135	127	12	meet	meet	VERB
fcis-2135	127	13	the	the	DET
fcis-2135	127	14	accuracy	accuracy	NOUN
fcis-2135	127	15	requirements	requirement	NOUN
fcis-2135	127	16	of	of	ADP
fcis-2135	127	17	complex	complex	ADJ
fcis-2135	127	18	motion	motion	NOUN
fcis-2135	127	19	model	model	NOUN
fcis-2135	127	20	testing	testing	NOUN
fcis-2135	127	21	.	.	PUNCT
fcis-2135	128	1	kooij	kooij	PROPN
fcis-2135	128	2	et	et	PROPN
fcis-2135	128	3	al	al	PROPN
fcis-2135	128	4	.	.	PUNCT
fcis-2135	129	1	[	[	X
fcis-2135	129	2	33	33	NUM
fcis-2135	129	3	]	]	PUNCT
fcis-2135	129	4	established	establish	VERB
fcis-2135	129	5	a	a	DET
fcis-2135	129	6	context	context	NOUN
fcis-2135	129	7	based	base	VERB
fcis-2135	129	8	dynamic	dynamic	ADJ
fcis-2135	129	9	bayesian	bayesian	NOUN
fcis-2135	129	10	network	network	NOUN
fcis-2135	129	11	(	(	PUNCT
fcis-2135	129	12	dbn	dbn	PROPN
fcis-2135	129	13	)	)	PUNCT
fcis-2135	129	14	model	model	NOUN
fcis-2135	129	15	for	for	ADP
fcis-2135	129	16	pedestrian	pedestrian	NOUN
fcis-2135	129	17	path	path	NOUN
fcis-2135	129	18	prediction	prediction	NOUN
fcis-2135	129	19	.	.	PUNCT
fcis-2135	130	1	this	this	DET
fcis-2135	130	2	model	model	NOUN
fcis-2135	130	3	combines	combine	VERB
fcis-2135	130	4	the	the	DET
fcis-2135	130	5	context	context	NOUN
fcis-2135	130	6	information	information	NOUN
fcis-2135	130	7	(	(	PUNCT
fcis-2135	130	8	pedestrian	pedestrian	NOUN
fcis-2135	130	9	head	head	NOUN
fcis-2135	130	10	direction	direction	NOUN
fcis-2135	130	11	,	,	PUNCT
fcis-2135	130	12	emergency	emergency	NOUN
fcis-2135	130	13	degree	degree	NOUN
fcis-2135	130	14	and	and	CCONJ
fcis-2135	130	15	environmental	environmental	ADJ
fcis-2135	130	16	space	space	NOUN
fcis-2135	130	17	layout	layout	PROPN
fcis-2135	130	18	)	)	PUNCT
fcis-2135	130	19	as	as	ADP
fcis-2135	130	20	the	the	DET
fcis-2135	130	21	potential	potential	ADJ
fcis-2135	130	22	state	state	NOUN
fcis-2135	130	23	to	to	ADP
fcis-2135	130	24	the	the	DET
fcis-2135	130	25	top	top	NOUN
fcis-2135	130	26	of	of	ADP
fcis-2135	130	27	the	the	DET
fcis-2135	130	28	slds	sld	NOUN
fcis-2135	130	29	model	model	NOUN
fcis-2135	130	30	,	,	PUNCT
fcis-2135	130	31	so	so	SCONJ
fcis-2135	130	32	as	as	SCONJ
fcis-2135	130	33	to	to	PART
fcis-2135	130	34	control	control	VERB
fcis-2135	130	35	the	the	DET
fcis-2135	130	36	switching	switch	VERB
fcis-2135	130	37	state	state	NOUN
fcis-2135	130	38	of	of	ADP
fcis-2135	130	39	the	the	DET
fcis-2135	130	40	slds	sld	NOUN
fcis-2135	130	41	model	model	NOUN
fcis-2135	130	42	.	.	PUNCT
fcis-2135	131	1	compared	compare	VERB
fcis-2135	131	2	with	with	ADP
fcis-2135	131	3	the	the	DET
fcis-2135	131	4	slds	sld	NOUN
fcis-2135	131	5	model	model	NOUN
fcis-2135	131	6	only	only	ADV
fcis-2135	131	7	,	,	PUNCT
fcis-2135	131	8	this	this	DET
fcis-2135	131	9	model	model	NOUN
fcis-2135	131	10	can	can	AUX
fcis-2135	131	11	make	make	VERB
fcis-2135	131	12	more	more	ADV
fcis-2135	131	13	accurate	accurate	ADJ
fcis-2135	131	14	predictions	prediction	NOUN
fcis-2135	131	15	.	.	PUNCT
fcis-2135	132	1	however	however	ADV
fcis-2135	132	2	,	,	PUNCT
fcis-2135	132	3	both	both	PRON
fcis-2135	132	4	slds	sld	NOUN
fcis-2135	132	5	model	model	NOUN
fcis-2135	132	6	-	-	PUNCT
fcis-2135	132	7	based	base	VERB
fcis-2135	132	8	prediction	prediction	NOUN
fcis-2135	132	9	methods	method	NOUN
fcis-2135	132	10	and	and	CCONJ
fcis-2135	132	11	dbn	dbn	PROPN
fcis-2135	132	12	modelbased	modelbase	VERB
fcis-2135	132	13	prediction	prediction	NOUN
fcis-2135	132	14	methods	method	NOUN
fcis-2135	132	15	always	always	ADV
fcis-2135	132	16	require	require	VERB
fcis-2135	132	17	a	a	DET
fcis-2135	132	18	lot	lot	NOUN
fcis-2135	132	19	of	of	ADP
fcis-2135	132	20	calculation	calculation	NOUN
fcis-2135	132	21	in	in	ADP
fcis-2135	132	22	the	the	DET
fcis-2135	132	23	process	process	NOUN
fcis-2135	132	24	of	of	ADP
fcis-2135	132	25	model	model	NOUN
fcis-2135	132	26	prediction	prediction	NOUN
fcis-2135	132	27	reasoning	reasoning	NOUN
fcis-2135	132	28	and	and	CCONJ
fcis-2135	132	29	mathematical	mathematical	ADJ
fcis-2135	132	30	model	model	NOUN
fcis-2135	132	31	building	building	NOUN
fcis-2135	132	32	,	,	PUNCT
fcis-2135	132	33	which	which	PRON
fcis-2135	132	34	is	be	AUX
fcis-2135	132	35	a	a	DET
fcis-2135	132	36	huge	huge	ADJ
fcis-2135	132	37	computing	computing	NOUN
fcis-2135	132	38	power	power	NOUN
fcis-2135	132	39	consumption	consumption	NOUN
fcis-2135	132	40	for	for	ADP
fcis-2135	132	41	computing	compute	VERB
fcis-2135	132	42	equipment	equipment	NOUN
fcis-2135	132	43	,	,	PUNCT
fcis-2135	132	44	and	and	CCONJ
fcis-2135	132	45	can	can	AUX
fcis-2135	132	46	not	not	PART
fcis-2135	132	47	well	well	ADV
fcis-2135	132	48	reflect	reflect	VERB
fcis-2135	132	49	additional	additional	ADJ
fcis-2135	132	50	scenes	scene	NOUN
fcis-2135	132	51	(	(	PUNCT
fcis-2135	132	52	such	such	ADJ
fcis-2135	132	53	as	as	ADP
fcis-2135	132	54	traffic	traffic	NOUN
fcis-2135	132	55	lights	light	NOUN
fcis-2135	132	56	,	,	PUNCT
fcis-2135	132	57	crosswalks	crosswalk	NOUN
fcis-2135	132	58	)	)	PUNCT
fcis-2135	132	59	and	and	CCONJ
fcis-2135	132	60	basic	basic	ADJ
fcis-2135	132	61	motion	motion	NOUN
fcis-2135	132	62	types	type	NOUN
fcis-2135	132	63	(	(	PUNCT
fcis-2135	132	64	such	such	ADJ
fcis-2135	132	65	as	as	ADP
fcis-2135	132	66	turning	turn	VERB
fcis-2135	132	67	)	)	PUNCT
fcis-2135	132	68	based	base	VERB
fcis-2135	132	69	on	on	ADP
fcis-2135	132	70	slds	sld	NOUN
fcis-2135	132	71	model	model	NOUN
fcis-2135	132	72	.	.	PUNCT
fcis-2135	133	1	helbing	helbe	VERB
fcis-2135	133	2	et	et	PROPN
fcis-2135	133	3	al	al	PROPN
fcis-2135	133	4	.	.	PUNCT
fcis-2135	134	1	[	[	X
fcis-2135	134	2	34	34	NUM
fcis-2135	134	3	]	]	PUNCT
fcis-2135	134	4	proposed	propose	VERB
fcis-2135	134	5	an	an	DET
fcis-2135	134	6	attractive	attractive	ADJ
fcis-2135	134	7	and	and	CCONJ
fcis-2135	134	8	repulsive	repulsive	ADJ
fcis-2135	134	9	pedestrian	pedestrian	NOUN
fcis-2135	134	10	motion	motion	NOUN
fcis-2135	134	11	model	model	NOUN
fcis-2135	134	12	,	,	PUNCT
fcis-2135	134	13	called	call	VERB
fcis-2135	134	14	the	the	DET
fcis-2135	134	15	social	social	ADJ
fcis-2135	134	16	force	force	NOUN
fcis-2135	134	17	model	model	NOUN
fcis-2135	134	18	.	.	PUNCT
fcis-2135	135	1	this	this	DET
fcis-2135	135	2	model	model	NOUN
fcis-2135	135	3	is	be	AUX
fcis-2135	135	4	widely	widely	ADV
fcis-2135	135	5	used	use	VERB
fcis-2135	135	6	in	in	ADP
fcis-2135	135	7	robotics	robotic	NOUN
fcis-2135	135	8	and	and	CCONJ
fcis-2135	135	9	activity	activity	NOUN
fcis-2135	135	10	understanding	understanding	NOUN
fcis-2135	135	11	[	[	X
fcis-2135	135	12	35	35	NUM
fcis-2135	135	13	]	]	PUNCT
fcis-2135	135	14	.	.	PUNCT
fcis-2135	136	1	alahi	alahi	PROPN
fcis-2135	136	2	et	et	PROPN
fcis-2135	136	3	al	al	PROPN
fcis-2135	136	4	.	.	PUNCT
fcis-2135	137	1	[	[	X
fcis-2135	137	2	36	36	NUM
fcis-2135	137	3	]	]	PUNCT
fcis-2135	137	4	proposed	propose	VERB
fcis-2135	137	5	presenting	present	VERB
fcis-2135	137	6	social	social	ADJ
fcis-2135	137	7	affinity	affinity	NOUN
fcis-2135	137	8	features	feature	NOUN
fcis-2135	137	9	by	by	ADP
fcis-2135	137	10	learning	learn	VERB
fcis-2135	137	11	their	their	PRON
fcis-2135	137	12	relative	relative	ADJ
fcis-2135	137	13	position	position	NOUN
fcis-2135	137	14	from	from	ADP
fcis-2135	137	15	pedestrian	pedestrian	NOUN
fcis-2135	137	16	trajectories	trajectory	NOUN
fcis-2135	137	17	in	in	ADP
fcis-2135	137	18	a	a	DET
fcis-2135	137	19	crowd	crowd	NOUN
fcis-2135	137	20	,	,	PUNCT
fcis-2135	137	21	while	while	SCONJ
fcis-2135	137	22	yi	yi	PROPN
fcis-2135	137	23	et	et	PROPN
fcis-2135	137	24	al	al	PROPN
fcis-2135	137	25	.	.	PUNCT
fcis-2135	138	1	[	[	X
fcis-2135	138	2	37	37	NUM
fcis-2135	138	3	]	]	PUNCT
fcis-2135	138	4	proposed	propose	VERB
fcis-2135	138	5	using	use	VERB
fcis-2135	138	6	human	human	ADJ
fcis-2135	138	7	attributes	attribute	NOUN
fcis-2135	138	8	to	to	PART
fcis-2135	138	9	improve	improve	VERB
fcis-2135	138	10	predictions	prediction	NOUN
fcis-2135	138	11	in	in	ADP
fcis-2135	138	12	a	a	DET
fcis-2135	138	13	crowd	crowd	NOUN
fcis-2135	138	14	.	.	PUNCT
fcis-2135	139	1	with	with	ADP
fcis-2135	139	2	the	the	DET
fcis-2135	139	3	rapid	rapid	ADJ
fcis-2135	139	4	development	development	NOUN
fcis-2135	139	5	of	of	ADP
fcis-2135	139	6	machine	machine	NOUN
fcis-2135	139	7	learning	learning	NOUN
fcis-2135	139	8	,	,	PUNCT
fcis-2135	139	9	kinematics	kinematics	NOUN
fcis-2135	139	10	-	-	PUNCT
fcis-2135	139	11	based	base	VERB
fcis-2135	139	12	methods	method	NOUN
fcis-2135	139	13	use	use	VERB
fcis-2135	139	14	some	some	DET
fcis-2135	139	15	machine	machine	NOUN
fcis-2135	139	16	learning	learning	NOUN
fcis-2135	139	17	-	-	PUNCT
fcis-2135	139	18	based	base	VERB
fcis-2135	139	19	tracking	tracking	NOUN
fcis-2135	139	20	algorithms	algorithm	NOUN
fcis-2135	139	21	to	to	PART
fcis-2135	139	22	improve	improve	VERB
fcis-2135	139	23	tracking	tracking	NOUN
fcis-2135	139	24	and	and	CCONJ
fcis-2135	139	25	prediction	prediction	NOUN
fcis-2135	139	26	when	when	SCONJ
fcis-2135	139	27	making	make	VERB
fcis-2135	139	28	predictions	prediction	NOUN
fcis-2135	139	29	,	,	PUNCT
fcis-2135	139	30	such	such	ADJ
fcis-2135	139	31	as	as	ADP
fcis-2135	139	32	kalman	kalman	PROPN
fcis-2135	139	33	filter	filter	PROPN
fcis-2135	139	34	(	(	PUNCT
fcis-2135	139	35	kf	kf	PROPN
fcis-2135	139	36	)	)	PUNCT
fcis-2135	139	37	,	,	PUNCT
fcis-2135	139	38	markov	markov	NOUN
fcis-2135	139	39	model	model	NOUN
fcis-2135	139	40	(	(	PUNCT
fcis-2135	139	41	mm	mm	NOUN
fcis-2135	139	42	)	)	PUNCT
fcis-2135	139	43	and	and	CCONJ
fcis-2135	139	44	gaussian	gaussian	ADJ
fcis-2135	139	45	process	process	NOUN
fcis-2135	139	46	[	[	X
fcis-2135	139	47	38	38	NUM
fcis-2135	139	48	]	]	PUNCT
fcis-2135	139	49	(	(	PUNCT
fcis-2135	139	50	gp	gp	NOUN
fcis-2135	139	51	)	)	PUNCT
fcis-2135	139	52	.	.	PUNCT
fcis-2135	140	1	the	the	DET
fcis-2135	140	2	advantage	advantage	NOUN
fcis-2135	140	3	of	of	ADP
fcis-2135	140	4	the	the	DET
fcis-2135	140	5	kf	kf	PROPN
fcis-2135	140	6	model	model	NOUN
fcis-2135	140	7	is	be	AUX
fcis-2135	140	8	that	that	SCONJ
fcis-2135	140	9	it	it	PRON
fcis-2135	140	10	can	can	AUX
fcis-2135	140	11	effectively	effectively	ADV
fcis-2135	140	12	process	process	VERB
fcis-2135	140	13	the	the	DET
fcis-2135	140	14	trajectory	trajectory	NOUN
fcis-2135	140	15	data	datum	NOUN
fcis-2135	140	16	of	of	ADP
fcis-2135	140	17	noise	noise	NOUN
fcis-2135	140	18	-	-	PUNCT
fcis-2135	140	19	free	free	ADJ
fcis-2135	140	20	points	point	NOUN
fcis-2135	140	21	when	when	SCONJ
fcis-2135	140	22	dealing	deal	VERB
fcis-2135	140	23	with	with	ADP
fcis-2135	140	24	the	the	DET
fcis-2135	140	25	pedestrian	pedestrian	NOUN
fcis-2135	140	26	trajectory	trajectory	NOUN
fcis-2135	140	27	prediction	prediction	NOUN
fcis-2135	140	28	problem	problem	NOUN
fcis-2135	140	29	,	,	PUNCT
fcis-2135	140	30	and	and	CCONJ
fcis-2135	140	31	has	have	VERB
fcis-2135	140	32	high	high	ADJ
fcis-2135	140	33	prediction	prediction	NOUN
fcis-2135	140	34	accuracy	accuracy	NOUN
fcis-2135	140	35	in	in	ADP
fcis-2135	140	36	a	a	DET
fcis-2135	140	37	short	short	ADJ
fcis-2135	140	38	time	time	NOUN
fcis-2135	140	39	.	.	PUNCT
fcis-2135	141	1	on	on	ADP
fcis-2135	141	2	the	the	DET
fcis-2135	141	3	contrary	contrary	NOUN
fcis-2135	141	4	,	,	PUNCT
fcis-2135	141	5	the	the	DET
fcis-2135	141	6	prediction	prediction	NOUN
fcis-2135	141	7	error	error	NOUN
fcis-2135	141	8	for	for	ADP
fcis-2135	141	9	a	a	DET
fcis-2135	141	10	long	long	ADJ
fcis-2135	141	11	time	time	NOUN
fcis-2135	141	12	is	be	AUX
fcis-2135	141	13	large	large	ADJ
fcis-2135	141	14	,	,	PUNCT
fcis-2135	141	15	and	and	CCONJ
fcis-2135	141	16	the	the	DET
fcis-2135	141	17	model	model	NOUN
fcis-2135	141	18	complexity	complexity	NOUN
fcis-2135	141	19	is	be	AUX
fcis-2135	141	20	high	high	ADJ
fcis-2135	141	21	,	,	PUNCT
fcis-2135	141	22	which	which	PRON
fcis-2135	141	23	seriously	seriously	ADV
fcis-2135	141	24	affects	affect	VERB
fcis-2135	141	25	the	the	DET
fcis-2135	141	26	prediction	prediction	NOUN
fcis-2135	141	27	accuracy	accuracy	NOUN
fcis-2135	141	28	.	.	PUNCT
fcis-2135	142	1	the	the	DET
fcis-2135	142	2	kf	kf	PROPN
fcis-2135	142	3	model	model	NOUN
fcis-2135	142	4	becomes	become	VERB
fcis-2135	142	5	more	more	ADV
fcis-2135	142	6	sensitive	sensitive	ADJ
fcis-2135	142	7	with	with	ADP
fcis-2135	142	8	the	the	DET
fcis-2135	142	9	increase	increase	NOUN
fcis-2135	142	10	of	of	ADP
fcis-2135	142	11	noise	noise	NOUN
fcis-2135	142	12	,	,	PUNCT
fcis-2135	142	13	and	and	CCONJ
fcis-2135	142	14	the	the	DET
fcis-2135	142	15	prediction	prediction	NOUN
fcis-2135	142	16	accuracy	accuracy	NOUN
fcis-2135	142	17	is	be	AUX
fcis-2135	142	18	approximately	approximately	ADV
fcis-2135	142	19	linearly	linearly	ADV
fcis-2135	142	20	reduced	reduce	VERB
fcis-2135	142	21	.	.	PUNCT
fcis-2135	143	1	the	the	DET
fcis-2135	143	2	mm	mm	PROPN
fcis-2135	143	3	has	have	VERB
fcis-2135	143	4	a	a	DET
fcis-2135	143	5	good	good	ADJ
fcis-2135	143	6	effect	effect	NOUN
fcis-2135	143	7	on	on	ADP
fcis-2135	143	8	the	the	DET
fcis-2135	143	9	state	state	NOUN
fcis-2135	143	10	prediction	prediction	NOUN
fcis-2135	143	11	of	of	ADP
fcis-2135	143	12	pedestrian	pedestrian	NOUN
fcis-2135	143	13	movement	movement	NOUN
fcis-2135	143	14	process	process	NOUN
fcis-2135	143	15	,	,	PUNCT
fcis-2135	143	16	but	but	CCONJ
fcis-2135	143	17	it	it	PRON
fcis-2135	143	18	is	be	AUX
fcis-2135	143	19	sensitive	sensitive	ADJ
fcis-2135	143	20	to	to	ADP
fcis-2135	143	21	the	the	DET
fcis-2135	143	22	fluctuation	fluctuation	NOUN
fcis-2135	143	23	of	of	ADP
fcis-2135	143	24	pedestrian	pedestrian	NOUN
fcis-2135	143	25	trajectory	trajectory	NOUN
fcis-2135	143	26	and	and	CCONJ
fcis-2135	143	27	is	be	AUX
fcis-2135	143	28	not	not	PART
fcis-2135	143	29	suitable	suitable	ADJ
fcis-2135	143	30	for	for	ADP
fcis-2135	143	31	medium	medium	ADJ
fcis-2135	143	32	and	and	CCONJ
fcis-2135	143	33	long	long	ADJ
fcis-2135	143	34	-	-	PUNCT
fcis-2135	143	35	term	term	NOUN
fcis-2135	143	36	pedestrian	pedestrian	NOUN
fcis-2135	143	37	trajectory	trajectory	NOUN
fcis-2135	143	38	prediction	prediction	NOUN
fcis-2135	143	39	.	.	PUNCT
fcis-2135	144	1	the	the	DET
fcis-2135	144	2	first	first	ADJ
fcis-2135	144	3	-	-	PUNCT
fcis-2135	144	4	order	order	NOUN
fcis-2135	144	5	mm	mm	NOUN
fcis-2135	144	6	only	only	ADV
fcis-2135	144	7	considers	consider	VERB
fcis-2135	144	8	the	the	DET
fcis-2135	144	9	influence	influence	NOUN
fcis-2135	144	10	of	of	ADP
fcis-2135	144	11	the	the	DET
fcis-2135	144	12	current	current	ADJ
fcis-2135	144	13	pedestrian	pedestrian	NOUN
fcis-2135	144	14	trajectory	trajectory	NOUN
fcis-2135	144	15	point	point	NOUN
fcis-2135	144	16	on	on	ADP
fcis-2135	144	17	the	the	DET
fcis-2135	144	18	future	future	ADJ
fcis-2135	144	19	trajectory	trajectory	NOUN
fcis-2135	144	20	point	point	NOUN
fcis-2135	144	21	,	,	PUNCT
fcis-2135	144	22	and	and	CCONJ
fcis-2135	144	23	the	the	DET
fcis-2135	144	24	data	data	NOUN
fcis-2135	144	25	information	information	NOUN
fcis-2135	144	26	of	of	ADP
fcis-2135	144	27	the	the	DET
fcis-2135	144	28	historical	historical	ADJ
fcis-2135	144	29	trajectory	trajectory	NOUN
fcis-2135	144	30	point	point	NOUN
fcis-2135	144	31	can	can	AUX
fcis-2135	144	32	not	not	PART
fcis-2135	144	33	be	be	AUX
fcis-2135	144	34	used	use	VERB
fcis-2135	144	35	as	as	ADV
fcis-2135	144	36	much	much	ADJ
fcis-2135	144	37	as	as	ADP
fcis-2135	144	38	possible	possible	ADJ
fcis-2135	144	39	,	,	PUNCT
fcis-2135	144	40	while	while	SCONJ
fcis-2135	144	41	the	the	DET
fcis-2135	144	42	high	high	ADJ
fcis-2135	144	43	-	-	PUNCT
fcis-2135	144	44	order	order	NOUN
fcis-2135	144	45	mm	mm	NOUN
fcis-2135	144	46	greatly	greatly	ADV
fcis-2135	144	47	increases	increase	VERB
fcis-2135	144	48	the	the	DET
fcis-2135	144	49	complexity	complexity	NOUN
fcis-2135	144	50	of	of	ADP
fcis-2135	144	51	the	the	DET
fcis-2135	144	52	model	model	NOUN
fcis-2135	144	53	calculation	calculation	NOUN
fcis-2135	144	54	.	.	PUNCT
fcis-2135	145	1	the	the	DET
fcis-2135	145	2	gp	gp	NOUN
fcis-2135	145	3	model	model	NOUN
fcis-2135	145	4	provides	provide	VERB
fcis-2135	145	5	a	a	DET
fcis-2135	145	6	non	non	ADJ
fcis-2135	145	7	-	-	ADJ
fcis-2135	145	8	parametric	parametric	ADJ
fcis-2135	145	9	model	model	NOUN
fcis-2135	145	10	for	for	ADP
fcis-2135	145	11	probability	probability	NOUN
fcis-2135	145	12	prediction	prediction	NOUN
fcis-2135	145	13	by	by	ADP
fcis-2135	145	14	assuming	assume	VERB
fcis-2135	145	15	that	that	SCONJ
fcis-2135	145	16	the	the	DET
fcis-2135	145	17	latent	latent	NOUN
fcis-2135	145	18	variables	variable	NOUN
fcis-2135	145	19	obey	obey	VERB
fcis-2135	145	20	the	the	DET
fcis-2135	145	21	gaussian	gaussian	ADJ
fcis-2135	145	22	distribution	distribution	NOUN
fcis-2135	145	23	.	.	PUNCT
fcis-2135	146	1	the	the	DET
fcis-2135	146	2	trajectory	trajectory	NOUN
fcis-2135	146	3	predicted	predict	VERB
fcis-2135	146	4	based	base	VERB
fcis-2135	146	5	on	on	ADP
fcis-2135	146	6	the	the	DET
fcis-2135	146	7	gp	gp	NOUN
fcis-2135	146	8	model	model	NOUN
fcis-2135	146	9	is	be	AUX
fcis-2135	146	10	learned	learn	VERB
fcis-2135	146	11	from	from	ADP
fcis-2135	146	12	the	the	DET
fcis-2135	146	13	historical	historical	ADJ
fcis-2135	146	14	trajectory	trajectory	NOUN
fcis-2135	146	15	data	datum	NOUN
fcis-2135	147	1	[	[	X
fcis-2135	147	2	39	39	NUM
fcis-2135	147	3	]	]	PUNCT
fcis-2135	147	4	,	,	PUNCT
fcis-2135	147	5	and	and	CCONJ
fcis-2135	147	6	the	the	DET
fcis-2135	147	7	uncertainty	uncertainty	NOUN
fcis-2135	147	8	involved	involve	VERB
fcis-2135	147	9	in	in	ADP
fcis-2135	147	10	the	the	DET
fcis-2135	147	11	trajectory	trajectory	NOUN
fcis-2135	147	12	modeling	modeling	NOUN
fcis-2135	147	13	of	of	ADP
fcis-2135	147	14	line	line	NOUN
fcis-2135	147	15	prediction	prediction	NOUN
fcis-2135	147	16	is	be	AUX
fcis-2135	147	17	clarified	clarify	VERB
fcis-2135	147	18	by	by	ADP
fcis-2135	147	19	specifying	specify	VERB
fcis-2135	147	20	an	an	DET
fcis-2135	147	21	appropriate	appropriate	ADJ
fcis-2135	147	22	kernel	kernel	NOUN
fcis-2135	147	23	function	function	NOUN
fcis-2135	147	24	in	in	ADP
fcis-2135	147	25	the	the	DET
fcis-2135	147	26	gp	gp	NOUN
fcis-2135	147	27	model	model	NOUN
fcis-2135	147	28	.	.	PUNCT
fcis-2135	148	1	gp	gp	NOUN
fcis-2135	148	2	model	model	NOUN
fcis-2135	148	3	can	can	AUX
fcis-2135	148	4	effectively	effectively	ADV
fcis-2135	148	5	predict	predict	VERB
fcis-2135	148	6	the	the	DET
fcis-2135	148	7	trajectory	trajectory	NOUN
fcis-2135	148	8	data	datum	NOUN
fcis-2135	148	9	with	with	ADP
fcis-2135	148	10	noise	noise	NOUN
fcis-2135	148	11	points	point	NOUN
fcis-2135	148	12	,	,	PUNCT
fcis-2135	148	13	and	and	CCONJ
fcis-2135	148	14	avoid	avoid	VERB
fcis-2135	148	15	the	the	DET
fcis-2135	148	16	lack	lack	NOUN
fcis-2135	148	17	of	of	ADP
fcis-2135	148	18	discrete	discrete	ADJ
fcis-2135	148	19	nature	nature	NOUN
fcis-2135	148	20	of	of	ADP
fcis-2135	148	21	trajectory	trajectory	NOUN
fcis-2135	148	22	data	datum	NOUN
fcis-2135	148	23	,	,	PUNCT
fcis-2135	148	24	and	and	CCONJ
fcis-2135	148	25	effectively	effectively	ADV
fcis-2135	148	26	express	express	VERB
fcis-2135	148	27	the	the	DET
fcis-2135	148	28	statistical	statistical	ADJ
fcis-2135	148	29	characteristics	characteristic	NOUN
fcis-2135	148	30	of	of	ADP
fcis-2135	148	31	pedestrian	pedestrian	NOUN
fcis-2135	148	32	trajectory	trajectory	NOUN
fcis-2135	148	33	distribution	distribution	NOUN
fcis-2135	148	34	.	.	PUNCT
fcis-2135	149	1	in	in	ADP
fcis-2135	149	2	summary	summary	NOUN
fcis-2135	149	3	,	,	PUNCT
fcis-2135	149	4	the	the	DET
fcis-2135	149	5	trajectory	trajectory	NOUN
fcis-2135	149	6	prediction	prediction	NOUN
fcis-2135	149	7	method	method	NOUN
fcis-2135	149	8	based	base	VERB
fcis-2135	149	9	on	on	ADP
fcis-2135	149	10	shallow	shallow	ADJ
fcis-2135	149	11	learning	learning	NOUN
fcis-2135	149	12	has	have	AUX
fcis-2135	149	13	achieved	achieve	VERB
fcis-2135	149	14	some	some	DET
fcis-2135	149	15	results	result	NOUN
fcis-2135	149	16	in	in	ADP
fcis-2135	149	17	the	the	DET
fcis-2135	149	18	early	early	ADJ
fcis-2135	149	19	stage	stage	NOUN
fcis-2135	149	20	and	and	CCONJ
fcis-2135	149	21	contributed	contribute	VERB
fcis-2135	149	22	to	to	ADP
fcis-2135	149	23	the	the	DET
fcis-2135	149	24	development	development	NOUN
fcis-2135	149	25	of	of	ADP
fcis-2135	149	26	pedestrian	pedestrian	NOUN
fcis-2135	149	27	trajectory	trajectory	NOUN
fcis-2135	149	28	prediction	prediction	NOUN
fcis-2135	149	29	.	.	PUNCT
fcis-2135	150	1	however	however	ADV
fcis-2135	150	2	,	,	PUNCT
fcis-2135	150	3	due	due	ADP
fcis-2135	150	4	to	to	ADP
fcis-2135	150	5	the	the	DET
fcis-2135	150	6	limitations	limitation	NOUN
fcis-2135	150	7	of	of	ADP
fcis-2135	150	8	kinematicsbased	kinematicsbase	VERB
fcis-2135	150	9	methods	method	NOUN
fcis-2135	150	10	,	,	PUNCT
fcis-2135	150	11	insufficient	insufficient	ADJ
fcis-2135	150	12	extraction	extraction	NOUN
fcis-2135	150	13	of	of	ADP
fcis-2135	150	14	motion	motion	NOUN
fcis-2135	150	15	feature	feature	NOUN
fcis-2135	150	16	information	information	NOUN
fcis-2135	150	17	,	,	PUNCT
fcis-2135	150	18	lack	lack	NOUN
fcis-2135	150	19	of	of	ADP
fcis-2135	150	20	specific	specific	ADJ
fcis-2135	150	21	scene	scene	NOUN
fcis-2135	150	22	information	information	NOUN
fcis-2135	150	23	,	,	PUNCT
fcis-2135	150	24	and	and	CCONJ
fcis-2135	150	25	complexity	complexity	NOUN
fcis-2135	150	26	of	of	ADP
fcis-2135	150	27	model	model	NOUN
fcis-2135	150	28	construction	construction	NOUN
fcis-2135	150	29	,	,	PUNCT
fcis-2135	150	30	there	there	PRON
fcis-2135	150	31	is	be	VERB
fcis-2135	150	32	a	a	DET
fcis-2135	150	33	big	big	ADJ
fcis-2135	150	34	gap	gap	NOUN
fcis-2135	150	35	between	between	ADP
fcis-2135	150	36	the	the	DET
fcis-2135	150	37	final	final	ADJ
fcis-2135	150	38	prediction	prediction	NOUN
fcis-2135	150	39	effect	effect	NOUN
fcis-2135	150	40	and	and	CCONJ
fcis-2135	150	41	the	the	DET
fcis-2135	150	42	actual	actual	ADJ
fcis-2135	150	43	situation	situation	NOUN
fcis-2135	150	44	.	.	PUNCT
fcis-2135	151	1	it	it	PRON
fcis-2135	151	2	is	be	AUX
fcis-2135	151	3	difficult	difficult	ADJ
fcis-2135	151	4	for	for	SCONJ
fcis-2135	151	5	traditional	traditional	ADJ
fcis-2135	151	6	methods	method	NOUN
fcis-2135	151	7	to	to	PART
fcis-2135	151	8	accurately	accurately	ADV
fcis-2135	151	9	predict	predict	VERB
fcis-2135	151	10	more	more	ADJ
fcis-2135	151	11	complex	complex	ADJ
fcis-2135	151	12	pedestrian	pedestrian	NOUN
fcis-2135	151	13	motion	motion	NOUN
fcis-2135	151	14	models	model	NOUN
fcis-2135	151	15	and	and	CCONJ
fcis-2135	151	16	scenes	scene	NOUN
fcis-2135	151	17	.	.	PUNCT
fcis-2135	152	1	3.2	3.2	NUM
fcis-2135	152	2	.	.	PUNCT
fcis-2135	152	3	trajectory	trajectory	NOUN
fcis-2135	152	4	prediction	prediction	NOUN
fcis-2135	152	5	method	method	NOUN
fcis-2135	152	6	based	base	VERB
fcis-2135	152	7	on	on	ADP
fcis-2135	152	8	deep	deep	ADJ
fcis-2135	152	9	learning	learning	NOUN
fcis-2135	152	10	trajectory	trajectory	NOUN
fcis-2135	152	11	prediction	prediction	NOUN
fcis-2135	152	12	methods	method	NOUN
fcis-2135	152	13	based	base	VERB
fcis-2135	152	14	on	on	ADP
fcis-2135	152	15	shallow	shallow	ADJ
fcis-2135	152	16	learning	learning	NOUN
fcis-2135	152	17	require	require	VERB
fcis-2135	152	18	complex	complex	ADJ
fcis-2135	152	19	and	and	CCONJ
fcis-2135	152	20	rigorous	rigorous	ADJ
fcis-2135	152	21	modeling	modeling	NOUN
fcis-2135	152	22	of	of	ADP
fcis-2135	152	23	the	the	DET
fcis-2135	152	24	model	model	NOUN
fcis-2135	152	25	,	,	PUNCT
fcis-2135	152	26	while	while	SCONJ
fcis-2135	152	27	trajectory	trajectory	NOUN
fcis-2135	152	28	prediction	prediction	NOUN
fcis-2135	152	29	methods	method	NOUN
fcis-2135	152	30	based	base	VERB
fcis-2135	152	31	on	on	ADP
fcis-2135	152	32	deep	deep	ADJ
fcis-2135	152	33	learning	learning	NOUN
fcis-2135	152	34	generally	generally	ADV
fcis-2135	152	35	do	do	AUX
fcis-2135	152	36	not	not	PART
fcis-2135	152	37	need	need	VERB
fcis-2135	152	38	to	to	PART
fcis-2135	152	39	assume	assume	VERB
fcis-2135	152	40	a	a	DET
fcis-2135	152	41	fixed	fix	VERB
fcis-2135	152	42	mathematical	mathematical	ADJ
fcis-2135	152	43	model	model	NOUN
fcis-2135	152	44	,	,	PUNCT
fcis-2135	152	45	and	and	CCONJ
fcis-2135	152	46	their	their	PRON
fcis-2135	152	47	networks	network	NOUN
fcis-2135	152	48	can	can	AUX
fcis-2135	152	49	learn	learn	VERB
fcis-2135	152	50	more	more	ADV
fcis-2135	152	51	reasonable	reasonable	ADJ
fcis-2135	152	52	mapping	mapping	NOUN
fcis-2135	152	53	relationships	relationship	NOUN
fcis-2135	152	54	with	with	ADP
fcis-2135	152	55	large	large	ADJ
fcis-2135	152	56	-	-	PUNCT
fcis-2135	152	57	scale	scale	NOUN
fcis-2135	152	58	data	data	NOUN
fcis-2135	152	59	sets	set	NOUN
fcis-2135	152	60	.	.	PUNCT
fcis-2135	153	1	in	in	ADP
fcis-2135	153	2	recent	recent	ADJ
fcis-2135	153	3	years	year	NOUN
fcis-2135	153	4	,	,	PUNCT
fcis-2135	153	5	with	with	ADP
fcis-2135	153	6	the	the	DET
fcis-2135	153	7	rise	rise	NOUN
fcis-2135	153	8	of	of	ADP
fcis-2135	153	9	deep	deep	ADJ
fcis-2135	153	10	learning	learning	NOUN
fcis-2135	153	11	,	,	PUNCT
fcis-2135	153	12	a	a	DET
fcis-2135	153	13	variety	variety	NOUN
fcis-2135	153	14	of	of	ADP
fcis-2135	153	15	models	model	NOUN
fcis-2135	153	16	for	for	ADP
fcis-2135	153	17	processing	processing	NOUN
fcis-2135	153	18	time	time	NOUN
fcis-2135	153	19	series	series	PROPN
fcis-2135	153	20	data	datum	NOUN
fcis-2135	153	21	have	have	AUX
fcis-2135	153	22	been	be	AUX
fcis-2135	153	23	proposed	propose	VERB
fcis-2135	153	24	,	,	PUNCT
fcis-2135	153	25	making	make	VERB
fcis-2135	153	26	trajectory	trajectory	NOUN
fcis-2135	153	27	prediction	prediction	NOUN
fcis-2135	153	28	algorithms	algorithm	NOUN
fcis-2135	153	29	based	base	VERB
fcis-2135	153	30	on	on	ADP
fcis-2135	153	31	neural	neural	ADJ
fcis-2135	153	32	networks	network	NOUN
fcis-2135	153	33	popular	popular	ADJ
fcis-2135	153	34	,	,	PUNCT
fcis-2135	153	35	and	and	CCONJ
fcis-2135	153	36	the	the	DET
fcis-2135	153	37	prediction	prediction	NOUN
fcis-2135	153	38	effect	effect	NOUN
fcis-2135	153	39	of	of	ADP
fcis-2135	153	40	these	these	DET
fcis-2135	153	41	algorithms	algorithm	NOUN
fcis-2135	153	42	has	have	AUX
fcis-2135	153	43	been	be	AUX
fcis-2135	153	44	greatly	greatly	ADV
fcis-2135	153	45	improved	improve	VERB
fcis-2135	153	46	compared	compare	VERB
fcis-2135	153	47	with	with	ADP
fcis-2135	153	48	traditional	traditional	ADJ
fcis-2135	153	49	algorithms	algorithm	NOUN
fcis-2135	153	50	.	.	PUNCT
fcis-2135	154	1	trajectory	trajectory	NOUN
fcis-2135	154	2	prediction	prediction	NOUN
fcis-2135	154	3	methods	method	NOUN
fcis-2135	154	4	based	base	VERB
fcis-2135	154	5	on	on	ADP
fcis-2135	154	6	deep	deep	ADJ
fcis-2135	154	7	learning	learning	NOUN
fcis-2135	154	8	mainly	mainly	ADV
fcis-2135	154	9	include	include	VERB
fcis-2135	154	10	three	three	NUM
fcis-2135	154	11	types	type	NOUN
fcis-2135	154	12	:	:	PUNCT
fcis-2135	154	13	trajectory	trajectory	NOUN
fcis-2135	154	14	prediction	prediction	NOUN
fcis-2135	154	15	method	method	NOUN
fcis-2135	154	16	based	base	VERB
fcis-2135	154	17	on	on	ADP
fcis-2135	154	18	rnn	rnn	PROPN
fcis-2135	154	19	,	,	PUNCT
fcis-2135	154	20	trajectory	trajectory	NOUN
fcis-2135	154	21	prediction	prediction	NOUN
fcis-2135	154	22	method	method	NOUN
fcis-2135	154	23	based	base	VERB
fcis-2135	154	24	on	on	ADP
fcis-2135	154	25	gan	gan	NOUN
fcis-2135	154	26	and	and	CCONJ
fcis-2135	154	27	trajectory	trajectory	NOUN
fcis-2135	154	28	prediction	prediction	NOUN
fcis-2135	154	29	method	method	NOUN
fcis-2135	154	30	based	base	VERB
fcis-2135	154	31	on	on	ADP
fcis-2135	154	32	gcn	gcn	PROPN
fcis-2135	154	33	.	.	PUNCT
fcis-2135	155	1	3.2.1	3.2.1	NUM
fcis-2135	155	2	.	.	PUNCT
fcis-2135	155	3	trajectory	trajectory	NOUN
fcis-2135	155	4	prediction	prediction	NOUN
fcis-2135	155	5	method	method	NOUN
fcis-2135	155	6	based	base	VERB
fcis-2135	155	7	on	on	ADP
fcis-2135	155	8	rnn	rnn	NOUN
fcis-2135	155	9	the	the	DET
fcis-2135	155	10	rnn	rnn	NOUN
fcis-2135	155	11	encodes	encode	VERB
fcis-2135	155	12	the	the	DET
fcis-2135	155	13	incoming	incoming	ADJ
fcis-2135	155	14	sequence	sequence	NOUN
fcis-2135	155	15	data	datum	NOUN
fcis-2135	155	16	into	into	ADP
fcis-2135	155	17	a	a	DET
fcis-2135	155	18	fixedsize	fixedsize	NOUN
fcis-2135	155	19	hidden	hide	VERB
fcis-2135	155	20	representation	representation	NOUN
fcis-2135	155	21	,	,	PUNCT
fcis-2135	155	22	and	and	CCONJ
fcis-2135	155	23	then	then	ADV
fcis-2135	155	24	uses	use	VERB
fcis-2135	155	25	another	another	DET
fcis-2135	155	26	rnn	rnn	NOUN
fcis-2135	155	27	to	to	PART
fcis-2135	155	28	decode	decode	VERB
fcis-2135	155	29	the	the	DET
fcis-2135	155	30	hidden	hide	VERB
fcis-2135	155	31	representation	representation	NOUN
fcis-2135	155	32	to	to	PART
fcis-2135	155	33	generate	generate	VERB
fcis-2135	155	34	a	a	DET
fcis-2135	155	35	sequential	sequential	ADJ
fcis-2135	155	36	time	time	NOUN
fcis-2135	155	37	representation	representation	NOUN
fcis-2135	155	38	of	of	ADP
fcis-2135	155	39	the	the	DET
fcis-2135	155	40	output	output	NOUN
fcis-2135	155	41	.	.	PUNCT
fcis-2135	156	1	although	although	SCONJ
fcis-2135	156	2	lstm	lstm	NOUN
fcis-2135	156	3	has	have	VERB
fcis-2135	156	4	the	the	DET
fcis-2135	156	5	ability	ability	NOUN
fcis-2135	156	6	to	to	PART
fcis-2135	156	7	learn	learn	VERB
fcis-2135	156	8	and	and	CCONJ
fcis-2135	156	9	replicate	replicate	VERB
fcis-2135	156	10	long	long	ADJ
fcis-2135	156	11	sequences	sequence	NOUN
fcis-2135	156	12	,	,	PUNCT
fcis-2135	156	13	they	they	PRON
fcis-2135	156	14	can	can	AUX
fcis-2135	156	15	not	not	PART
fcis-2135	156	16	capture	capture	VERB
fcis-2135	156	17	dependencies	dependency	NOUN
fcis-2135	156	18	between	between	ADP
fcis-2135	156	19	multiple	multiple	ADJ
fcis-2135	156	20	related	relate	VERB
fcis-2135	156	21	sequences	sequence	NOUN
fcis-2135	156	22	.	.	PUNCT
fcis-2135	157	1	to	to	ADP
fcis-2135	157	2	this	this	DET
fcis-2135	157	3	end	end	NOUN
fcis-2135	157	4	,	,	PUNCT
fcis-2135	157	5	the	the	DET
fcis-2135	157	6	social	social	ADJ
fcis-2135	157	7	pooling	pooling	NOUN
fcis-2135	157	8	layer	layer	NOUN
fcis-2135	157	9	of	of	ADP
fcis-2135	157	10	s	s	NOUN
fcis-2135	157	11	-	-	PUNCT
fcis-2135	157	12	lstm	lstm	ADJ
fcis-2135	157	13	[	[	X
fcis-2135	157	14	20	20	NUM
fcis-2135	157	15	]	]	PUNCT
fcis-2135	157	16	was	be	AUX
fcis-2135	157	17	proposed	propose	VERB
fcis-2135	157	18	to	to	PART
fcis-2135	157	19	heuristically	heuristically	ADV
fcis-2135	157	20	aggregate	aggregate	VERB
fcis-2135	157	21	the	the	DET
fcis-2135	157	22	information	information	NOUN
fcis-2135	157	23	of	of	ADP
fcis-2135	157	24	neighborhood	neighborhood	NOUN
fcis-2135	157	25	pedestrians	pedestrian	NOUN
fcis-2135	157	26	.	.	PUNCT
fcis-2135	158	1	s	s	X
fcis-2135	158	2	-	-	PUNCT
fcis-2135	158	3	lstm	lstm	ADJ
fcis-2135	158	4	is	be	AUX
fcis-2135	158	5	the	the	DET
fcis-2135	158	6	first	first	ADJ
fcis-2135	158	7	application	application	NOUN
fcis-2135	158	8	of	of	ADP
fcis-2135	158	9	recurrent	recurrent	ADJ
fcis-2135	158	10	neural	neural	ADJ
fcis-2135	158	11	networks	network	NOUN
fcis-2135	158	12	to	to	PART
fcis-2135	158	13	simulate	simulate	VERB
fcis-2135	158	14	human	human	NOUN
fcis-2135	158	15	-	-	PUNCT
fcis-2135	158	16	to	to	ADP
fcis-2135	158	17	-	-	PUNCT
fcis-2135	158	18	human	human	ADJ
fcis-2135	158	19	interaction	interaction	NOUN
fcis-2135	158	20	in	in	ADP
fcis-2135	158	21	crowded	crowded	ADJ
fcis-2135	158	22	scenes	scene	NOUN
fcis-2135	158	23	and	and	CCONJ
fcis-2135	158	24	has	have	AUX
fcis-2135	158	25	become	become	VERB
fcis-2135	158	26	a	a	DET
fcis-2135	158	27	baseline	baseline	NOUN
fcis-2135	158	28	for	for	ADP
fcis-2135	158	29	pedestrian	pedestrian	NOUN
fcis-2135	158	30	trajectory	trajectory	NOUN
fcis-2135	158	31	prediction	prediction	NOUN
fcis-2135	158	32	.	.	PUNCT
fcis-2135	159	1	the	the	DET
fcis-2135	159	2	comparison	comparison	NOUN
fcis-2135	159	3	of	of	ADP
fcis-2135	159	4	pedestrian	pedestrian	NOUN
fcis-2135	159	5	trajectory	trajectory	NOUN
fcis-2135	159	6	prediction	prediction	NOUN
fcis-2135	159	7	methods	method	NOUN
fcis-2135	159	8	based	base	VERB
fcis-2135	159	9	on	on	ADP
fcis-2135	159	10	rnn	rnn	PROPN
fcis-2135	159	11	is	be	AUX
fcis-2135	159	12	shown	show	VERB
fcis-2135	159	13	in	in	ADP
fcis-2135	159	14	table	table	NOUN
fcis-2135	159	15	1	1	NUM
fcis-2135	159	16	.	.	PUNCT
fcis-2135	160	1	according	accord	VERB
fcis-2135	160	2	to	to	ADP
fcis-2135	160	3	the	the	DET
fcis-2135	160	4	way	way	NOUN
fcis-2135	160	5	of	of	ADP
fcis-2135	160	6	obtaining	obtain	VERB
fcis-2135	160	7	neighbor	neighbor	ADJ
fcis-2135	160	8	information	information	NOUN
fcis-2135	160	9	,	,	PUNCT
fcis-2135	160	10	the	the	DET
fcis-2135	160	11	prediction	prediction	NOUN
fcis-2135	160	12	model	model	NOUN
fcis-2135	160	13	can	can	AUX
fcis-2135	160	14	be	be	AUX
fcis-2135	160	15	divided	divide	VERB
fcis-2135	160	16	into	into	ADP
fcis-2135	160	17	models	model	NOUN
fcis-2135	160	18	based	base	VERB
fcis-2135	160	19	on	on	ADP
fcis-2135	160	20	current	current	ADJ
fcis-2135	160	21	results	result	NOUN
fcis-2135	160	22	(	(	PUNCT
fcis-2135	160	23	speed	speed	NOUN
fcis-2135	160	24	,	,	PUNCT
fcis-2135	160	25	location	location	NOUN
fcis-2135	160	26	,	,	PUNCT
fcis-2135	160	27	etc	etc	X
fcis-2135	160	28	.	.	X
fcis-2135	160	29	)	)	PUNCT
fcis-2135	161	1	[	[	X
fcis-2135	161	2	13,22,40	13,22,40	NUM
fcis-2135	161	3	-	-	SYM
fcis-2135	161	4	41	41	NUM
fcis-2135	161	5	]	]	PUNCT
fcis-2135	161	6	and	and	CCONJ
fcis-2135	161	7	models	model	NOUN
fcis-2135	161	8	based	base	VERB
fcis-2135	161	9	on	on	ADP
fcis-2135	161	10	previous	previous	ADJ
fcis-2135	161	11	states	state	NOUN
fcis-2135	161	12	[	[	X
fcis-2135	161	13	13,20,40	13,20,40	NUM
fcis-2135	161	14	-	-	ADJ
fcis-2135	161	15	41,42	41,42	NOUN
fcis-2135	161	16	-	-	PUNCT
fcis-2135	161	17	46	46	NUM
fcis-2135	161	18	]	]	PUNCT
fcis-2135	161	19	.	.	PUNCT
fcis-2135	162	1	in	in	ADP
fcis-2135	162	2	order	order	NOUN
fcis-2135	162	3	to	to	PART
fcis-2135	162	4	distinguish	distinguish	VERB
fcis-2135	162	5	the	the	DET
fcis-2135	162	6	importance	importance	NOUN
fcis-2135	162	7	of	of	ADP
fcis-2135	162	8	neighbors	neighbor	NOUN
fcis-2135	162	9	around	around	ADP
fcis-2135	162	10	pedestrians	pedestrian	NOUN
fcis-2135	162	11	,	,	PUNCT
fcis-2135	162	12	some	some	DET
fcis-2135	162	13	rnn	rnn	NOUN
fcis-2135	162	14	-	-	PUNCT
fcis-2135	162	15	based	base	VERB
fcis-2135	162	16	pedestrian	pedestrian	NOUN
fcis-2135	162	17	trajectory	trajectory	NOUN
fcis-2135	162	18	prediction	prediction	NOUN
fcis-2135	162	19	methods	method	NOUN
fcis-2135	162	20	use	use	VERB
fcis-2135	162	21	the	the	DET
fcis-2135	162	22	attention	attention	NOUN
fcis-2135	162	23	mechanism	mechanism	NOUN
fcis-2135	162	24	to	to	PART
fcis-2135	162	25	provide	provide	VERB
fcis-2135	162	26	different	different	ADJ
fcis-2135	162	27	ways	way	NOUN
fcis-2135	162	28	for	for	ADP
fcis-2135	162	29	calculating	calculate	VERB
fcis-2135	162	30	the	the	DET
fcis-2135	162	31	weights	weight	NOUN
fcis-2135	162	32	of	of	ADP
fcis-2135	162	33	neighbors	neighbor	NOUN
fcis-2135	162	34	.	.	PUNCT
fcis-2135	163	1	for	for	ADP
fcis-2135	163	2	example	example	NOUN
fcis-2135	163	3	,	,	PUNCT
fcis-2135	163	4	the	the	DET
fcis-2135	163	5	soft	soft	ADJ
fcis-2135	163	6	attention	attention	NOUN
fcis-2135	163	7	score	score	NOUN
fcis-2135	163	8	is	be	AUX
fcis-2135	163	9	calculated	calculate	VERB
fcis-2135	163	10	based	base	VERB
fcis-2135	163	11	on	on	ADP
fcis-2135	163	12	the	the	DET
fcis-2135	163	13	hidden	hidden	ADJ
fcis-2135	163	14	state	state	NOUN
fcis-2135	163	15	,	,	PUNCT
fcis-2135	163	16	and	and	CCONJ
fcis-2135	163	17	the	the	DET
fcis-2135	163	18	pairwise	pairwise	NOUN
fcis-2135	163	19	speed	speed	NOUN
fcis-2135	163	20	correlation	correlation	NOUN
fcis-2135	163	21	is	be	AUX
fcis-2135	163	22	calculated	calculate	VERB
fcis-2135	163	23	[	[	X
fcis-2135	163	24	42	42	NUM
fcis-2135	163	25	,	,	PUNCT
fcis-2135	163	26	45	45	NUM
fcis-2135	163	27	]	]	PUNCT
fcis-2135	163	28	,	,	PUNCT
fcis-2135	163	29	using	use	VERB
fcis-2135	163	30	an	an	DET
fcis-2135	163	31	attention	attention	NOUN
fcis-2135	163	32	model	model	NOUN
fcis-2135	163	33	that	that	PRON
fcis-2135	163	34	combines	combine	VERB
fcis-2135	163	35	'	'	PART
fcis-2135	163	36	soft	soft	ADJ
fcis-2135	163	37	attention	attention	NOUN
fcis-2135	163	38	'	'	PUNCT
fcis-2135	163	39	and	and	CCONJ
fcis-2135	163	40	'	'	PUNCT
fcis-2135	163	41	hard	hard	ADJ
fcis-2135	163	42	attention	attention	NOUN
fcis-2135	163	43	'	'	PUNCT
fcis-2135	163	44	.	.	PUNCT
fcis-2135	164	1	based	base	VERB
fcis-2135	164	2	on	on	ADP
fcis-2135	164	3	lstm	lstm	PROPN
fcis-2135	164	4	's	's	PART
fcis-2135	164	5	position	position	NOUN
fcis-2135	164	6	-	-	PUNCT
fcis-2135	164	7	velocity	velocity	NOUN
fcis-2135	164	8	-	-	PUNCT
fcis-2135	164	9	timeattention	timeattention	NOUN
fcis-2135	164	10	model	model	NOUN
fcis-2135	164	11	[	[	X
fcis-2135	164	12	47	47	NUM
fcis-2135	164	13	]	]	PUNCT
fcis-2135	164	14	,	,	PUNCT
fcis-2135	164	15	two	two	NUM
fcis-2135	164	16	temporal	temporal	ADJ
fcis-2135	164	17	attention	attention	NOUN
fcis-2135	164	18	mechanisms	mechanism	NOUN
fcis-2135	164	19	are	be	AUX
fcis-2135	164	20	designed	design	VERB
fcis-2135	164	21	to	to	PART
fcis-2135	164	22	calculate	calculate	VERB
fcis-2135	164	23	the	the	DET
fcis-2135	164	24	hidden	hide	VERB
fcis-2135	164	25	state	state	NOUN
fcis-2135	164	26	vectors	vector	NOUN
fcis-2135	164	27	of	of	ADP
fcis-2135	164	28	the	the	DET
fcis-2135	164	29	position	position	NOUN
fcis-2135	164	30	and	and	CCONJ
fcis-2135	164	31	velocity	velocity	NOUN
fcis-2135	165	1	lstm	lstm	NOUN
fcis-2135	165	2	layers	layer	NOUN
fcis-2135	165	3	.	.	PUNCT
fcis-2135	166	1	the	the	DET
fcis-2135	166	2	application	application	NOUN
fcis-2135	166	3	of	of	ADP
fcis-2135	166	4	attention	attention	NOUN
fcis-2135	166	5	mechanism	mechanism	NOUN
fcis-2135	166	6	enhances	enhance	VERB
fcis-2135	166	7	the	the	DET
fcis-2135	166	8	interaction	interaction	NOUN
fcis-2135	166	9	between	between	ADP
fcis-2135	166	10	pedestrians	pedestrian	NOUN
fcis-2135	166	11	and	and	CCONJ
fcis-2135	166	12	improves	improve	VERB
fcis-2135	166	13	the	the	DET
fcis-2135	166	14	credibility	credibility	NOUN
fcis-2135	166	15	of	of	ADP
fcis-2135	166	16	trajectory	trajectory	NOUN
fcis-2135	166	17	prediction	prediction	NOUN
fcis-2135	166	18	.	.	PUNCT
fcis-2135	167	1	the	the	DET
fcis-2135	167	2	rnn	rnn	PROPN
fcis-2135	167	3	72	72	NUM
fcis-2135	167	4	based	base	VERB
fcis-2135	167	5	model	model	NOUN
fcis-2135	167	6	has	have	VERB
fcis-2135	167	7	the	the	DET
fcis-2135	167	8	problems	problem	NOUN
fcis-2135	167	9	of	of	ADP
fcis-2135	167	10	gradient	gradient	ADJ
fcis-2135	167	11	disappearance	disappearance	NOUN
fcis-2135	167	12	and	and	CCONJ
fcis-2135	167	13	difficulty	difficulty	NOUN
fcis-2135	167	14	in	in	ADP
fcis-2135	167	15	expansion	expansion	NOUN
fcis-2135	167	16	during	during	ADP
fcis-2135	167	17	training	training	NOUN
fcis-2135	167	18	.	.	PUNCT
fcis-2135	168	1	many	many	ADJ
fcis-2135	168	2	predictions	prediction	NOUN
fcis-2135	168	3	work	work	VERB
fcis-2135	168	4	combines	combine	VERB
fcis-2135	168	5	convolutional	convolutional	ADJ
fcis-2135	168	6	neural	neural	ADJ
fcis-2135	168	7	network	network	NOUN
fcis-2135	168	8	(	(	PUNCT
fcis-2135	168	9	cnn	cnn	PROPN
fcis-2135	168	10	)	)	PUNCT
fcis-2135	168	11	,	,	PUNCT
fcis-2135	168	12	which	which	PRON
fcis-2135	168	13	confirms	confirm	VERB
fcis-2135	168	14	that	that	SCONJ
fcis-2135	168	15	cnn	cnn	PROPN
fcis-2135	168	16	is	be	AUX
fcis-2135	168	17	competitive	competitive	ADJ
fcis-2135	168	18	in	in	ADP
fcis-2135	168	19	trajectory	trajectory	NOUN
fcis-2135	168	20	prediction	prediction	NOUN
fcis-2135	168	21	.	.	PUNCT
fcis-2135	169	1	however	however	ADV
fcis-2135	169	2	,	,	PUNCT
fcis-2135	169	3	it	it	PRON
fcis-2135	169	4	can	can	AUX
fcis-2135	169	5	not	not	PART
fcis-2135	169	6	simulate	simulate	VERB
fcis-2135	169	7	spatial	spatial	ADJ
fcis-2135	169	8	interaction	interaction	NOUN
fcis-2135	169	9	between	between	ADP
fcis-2135	169	10	pedestrians	pedestrian	NOUN
fcis-2135	169	11	.	.	PUNCT
fcis-2135	170	1	in	in	ADP
fcis-2135	170	2	addition	addition	NOUN
fcis-2135	170	3	,	,	PUNCT
fcis-2135	170	4	some	some	DET
fcis-2135	170	5	models	model	NOUN
fcis-2135	170	6	combine	combine	AUX
fcis-2135	170	7	rnn	rnn	VERB
fcis-2135	170	8	with	with	ADP
fcis-2135	170	9	other	other	ADJ
fcis-2135	170	10	structures	structure	NOUN
fcis-2135	170	11	.	.	PUNCT
fcis-2135	171	1	for	for	ADP
fcis-2135	171	2	example	example	NOUN
fcis-2135	171	3	,	,	PUNCT
fcis-2135	171	4	the	the	DET
fcis-2135	171	5	gaussian	gaussian	ADJ
fcis-2135	171	6	process	process	NOUN
fcis-2135	171	7	[	[	X
fcis-2135	171	8	48	48	NUM
fcis-2135	171	9	]	]	PUNCT
fcis-2135	171	10	is	be	AUX
fcis-2135	171	11	combined	combine	VERB
fcis-2135	171	12	to	to	PART
fcis-2135	171	13	predict	predict	VERB
fcis-2135	171	14	the	the	DET
fcis-2135	171	15	complete	complete	ADJ
fcis-2135	171	16	distribution	distribution	NOUN
fcis-2135	171	17	of	of	ADP
fcis-2135	171	18	pedestrian	pedestrian	NOUN
fcis-2135	171	19	future	future	ADJ
fcis-2135	171	20	trajectories	trajectory	NOUN
fcis-2135	171	21	.	.	PUNCT
fcis-2135	172	1	due	due	ADP
fcis-2135	172	2	to	to	ADP
fcis-2135	172	3	the	the	DET
fcis-2135	172	4	uncertainty	uncertainty	NOUN
fcis-2135	172	5	of	of	ADP
fcis-2135	172	6	the	the	DET
fcis-2135	172	7	future	future	NOUN
fcis-2135	172	8	,	,	PUNCT
fcis-2135	172	9	cgns	cgn	NOUN
fcis-2135	172	10	[	[	X
fcis-2135	172	11	46	46	NUM
fcis-2135	172	12	]	]	PUNCT
fcis-2135	172	13	used	use	VERB
fcis-2135	172	14	gru	gru	PROPN
fcis-2135	172	15	to	to	PART
fcis-2135	172	16	infer	infer	VERB
fcis-2135	172	17	from	from	ADP
fcis-2135	172	18	the	the	DET
fcis-2135	172	19	perspective	perspective	NOUN
fcis-2135	172	20	of	of	ADP
fcis-2135	172	21	probability	probability	NOUN
fcis-2135	172	22	and	and	CCONJ
fcis-2135	172	23	proposed	propose	VERB
fcis-2135	172	24	feasible	feasible	ADJ
fcis-2135	172	25	hypotheses	hypothesis	NOUN
fcis-2135	172	26	.	.	PUNCT
fcis-2135	173	1	table	table	NOUN
fcis-2135	173	2	1	1	NUM
fcis-2135	173	3	.	.	PUNCT
fcis-2135	173	4	comparison	comparison	NOUN
fcis-2135	173	5	of	of	ADP
fcis-2135	173	6	pedestrian	pedestrian	NOUN
fcis-2135	173	7	trajectory	trajectory	NOUN
fcis-2135	173	8	prediction	prediction	NOUN
fcis-2135	173	9	methods	method	NOUN
fcis-2135	173	10	based	base	VERB
fcis-2135	173	11	on	on	ADP
fcis-2135	173	12	rnn	rnn	NOUN
fcis-2135	173	13	method	method	PROPN
fcis-2135	173	14	advantage	advantage	NOUN
fcis-2135	173	15	shortcoming	shortcoming	NOUN
fcis-2135	173	16	research	research	NOUN
fcis-2135	173	17	direction	direction	NOUN
fcis-2135	173	18	loss	loss	NOUN
fcis-2135	173	19	function	function	NOUN
fcis-2135	173	20	ss	ss	NOUN
fcis-2135	173	21	-	-	NOUN
fcis-2135	173	22	lstm	lstm	NOUN
fcis-2135	173	23	[	[	X
fcis-2135	173	24	19	19	NUM
fcis-2135	173	25	]	]	X
fcis-2135	173	26	scene	scene	NOUN
fcis-2135	173	27	layout	layout	NOUN
fcis-2135	173	28	lack	lack	NOUN
fcis-2135	173	29	of	of	ADP
fcis-2135	173	30	interaction	interaction	NOUN
fcis-2135	173	31	attention	attention	NOUN
fcis-2135	173	32	mechanism	mechanism	NOUN
fcis-2135	173	33	mean	mean	VERB
fcis-2135	173	34	square	square	ADJ
fcis-2135	173	35	error	error	NOUN
fcis-2135	173	36	s	s	NOUN
fcis-2135	173	37	-	-	PUNCT
fcis-2135	173	38	lstm	lstm	ADJ
fcis-2135	173	39	[	[	X
fcis-2135	173	40	20	20	NUM
fcis-2135	173	41	]	]	X
fcis-2135	173	42	social	social	ADJ
fcis-2135	173	43	pooling	pool	VERB
fcis-2135	173	44	local	local	ADJ
fcis-2135	173	45	interaction	interaction	NOUN
fcis-2135	173	46	interactive	interactive	ADJ
fcis-2135	173	47	optimization	optimization	NOUN
fcis-2135	173	48	negative	negative	ADJ
fcis-2135	173	49	logarithmic	logarithmic	ADJ
fcis-2135	173	50	likelihood	likelihood	NOUN
fcis-2135	173	51	st	st	NOUN
fcis-2135	173	52	-	-	PUNCT
fcis-2135	173	53	lstm	lstm	NOUN
fcis-2135	173	54	[	[	X
fcis-2135	173	55	21	21	NUM
fcis-2135	173	56	]	]	PUNCT
fcis-2135	173	57	spatiotemporal	spatiotemporal	ADJ
fcis-2135	173	58	recursion	recursion	NOUN
fcis-2135	173	59	loss	loss	NOUN
fcis-2135	173	60	of	of	ADP
fcis-2135	173	61	interaction	interaction	NOUN
fcis-2135	173	62	perceptual	perceptual	ADJ
fcis-2135	173	63	interaction	interaction	NOUN
fcis-2135	173	64	negative	negative	ADJ
fcis-2135	173	65	logarithmic	logarithmic	ADJ
fcis-2135	173	66	likelihood	likelihood	NOUN
fcis-2135	173	67	sr	sr	PROPN
fcis-2135	173	68	-	-	PUNCT
fcis-2135	173	69	lstm	lstm	PROPN
fcis-2135	173	70	[	[	X
fcis-2135	173	71	22	22	NUM
fcis-2135	173	72	]	]	PUNCT
fcis-2135	173	73	refinement	refinement	NOUN
fcis-2135	173	74	of	of	ADP
fcis-2135	173	75	intention	intention	NOUN
fcis-2135	173	76	data	datum	NOUN
fcis-2135	173	77	deviation	deviation	NOUN
fcis-2135	173	78	strong	strong	ADJ
fcis-2135	173	79	adaptability	adaptability	NOUN
fcis-2135	173	80	mean	mean	VERB
fcis-2135	173	81	square	square	ADJ
fcis-2135	173	82	error	error	NOUN
fcis-2135	173	83	desire	desire	NOUN
fcis-2135	174	1	[	[	X
fcis-2135	174	2	40	40	NUM
fcis-2135	174	3	]	]	PUNCT
fcis-2135	174	4	inverse	inverse	NOUN
fcis-2135	174	5	optimal	optimal	ADJ
fcis-2135	174	6	control	control	NOUN
fcis-2135	174	7	spatial	spatial	ADJ
fcis-2135	174	8	constraints	constraint	NOUN
fcis-2135	174	9	social	social	PROPN
fcis-2135	174	10	association	association	PROPN
fcis-2135	174	11	cross	cross	PROPN
fcis-2135	174	12	entropy	entropy	PROPN
fcis-2135	174	13	regression	regression	PROPN
fcis-2135	174	14	s	s	NOUN
fcis-2135	174	15	-	-	NOUN
fcis-2135	174	16	attention	attention	NOUN
fcis-2135	174	17	[	[	X
fcis-2135	174	18	41	41	NUM
fcis-2135	174	19	]	]	X
fcis-2135	174	20	social	social	ADJ
fcis-2135	174	21	attention	attention	NOUN
fcis-2135	174	22	maintain	maintain	VERB
fcis-2135	174	23	the	the	DET
fcis-2135	174	24	whole	whole	ADJ
fcis-2135	174	25	drawing	drawing	NOUN
fcis-2135	174	26	optimize	optimize	NOUN
fcis-2135	174	27	promotion	promotion	NOUN
fcis-2135	174	28	negative	negative	ADJ
fcis-2135	174	29	logarithmic	logarithmic	ADJ
fcis-2135	174	30	likelihood	likelihood	NOUN
fcis-2135	174	31	mx	mx	NOUN
fcis-2135	174	32	-	-	NOUN
fcis-2135	174	33	lstm	lstm	ADJ
fcis-2135	174	34	[	[	X
fcis-2135	174	35	42	42	NUM
fcis-2135	174	36	]	]	X
fcis-2135	174	37	joint	joint	ADJ
fcis-2135	174	38	forecasting	forecasting	NOUN
fcis-2135	174	39	narrow	narrow	ADJ
fcis-2135	174	40	promotion	promotion	NOUN
fcis-2135	174	41	enrich	enrich	VERB
fcis-2135	174	42	the	the	DET
fcis-2135	174	43	scene	scene	NOUN
fcis-2135	175	1	negative	negative	ADJ
fcis-2135	175	2	logarithmic	logarithmic	ADJ
fcis-2135	175	3	likelihood	likelihood	NOUN
fcis-2135	175	4	sns	sns	PROPN
fcis-2135	175	5	-	-	PUNCT
fcis-2135	175	6	lstm	lstm	PROPN
fcis-2135	175	7	[	[	X
fcis-2135	175	8	43	43	NUM
fcis-2135	175	9	]	]	PUNCT
fcis-2135	175	10	multimode	multimode	NOUN
fcis-2135	175	11	input	input	NOUN
fcis-2135	175	12	pay	pay	VERB
fcis-2135	175	13	attention	attention	NOUN
fcis-2135	175	14	to	to	ADP
fcis-2135	175	15	average	average	ADJ
fcis-2135	175	16	application	application	NOUN
fcis-2135	175	17	promotion	promotion	NOUN
fcis-2135	175	18	negative	negative	ADJ
fcis-2135	175	19	logarithmic	logarithmic	ADJ
fcis-2135	175	20	likelihood	likelihood	NOUN
fcis-2135	175	21	varshneya[44	varshneya[44	VERB
fcis-2135	175	22	]	]	PUNCT
fcis-2135	175	23	extent	extent	NOUN
fcis-2135	175	24	pooling	pool	VERB
fcis-2135	175	25	various	various	ADJ
fcis-2135	175	26	parameters	parameter	NOUN
fcis-2135	175	27	multi	multi	ADJ
fcis-2135	175	28	class	class	NOUN
fcis-2135	175	29	objects	object	VERB
fcis-2135	175	30	negative	negative	ADJ
fcis-2135	175	31	logarithmic	logarithmic	ADJ
fcis-2135	175	32	likelihood	likelihood	NOUN
fcis-2135	175	33	fernando	fernando	NOUN
fcis-2135	176	1	[	[	X
fcis-2135	176	2	45	45	NUM
fcis-2135	176	3	]	]	PUNCT
fcis-2135	176	4	soft	soft	ADJ
fcis-2135	176	5	and	and	CCONJ
fcis-2135	176	6	hard	hard	ADJ
fcis-2135	176	7	attention	attention	NOUN
fcis-2135	176	8	local	local	ADJ
fcis-2135	176	9	interaction	interaction	NOUN
fcis-2135	176	10	domain	domain	NOUN
fcis-2135	176	11	expansion	expansion	NOUN
fcis-2135	176	12	mean	mean	VERB
fcis-2135	176	13	square	square	ADJ
fcis-2135	176	14	error	error	NOUN
fcis-2135	176	15	3.2.2	3.2.2	NUM
fcis-2135	176	16	.	.	PUNCT
fcis-2135	176	17	prediction	prediction	NOUN
fcis-2135	176	18	method	method	NOUN
fcis-2135	176	19	based	base	VERB
fcis-2135	176	20	on	on	ADP
fcis-2135	176	21	gan	gan	PROPN
fcis-2135	176	22	gan	gan	PROPN
fcis-2135	176	23	-	-	PUNCT
fcis-2135	176	24	based	base	VERB
fcis-2135	176	25	pedestrian	pedestrian	NOUN
fcis-2135	176	26	trajectory	trajectory	NOUN
fcis-2135	176	27	prediction	prediction	NOUN
fcis-2135	176	28	method	method	NOUN
fcis-2135	176	29	introduces	introduce	VERB
fcis-2135	176	30	the	the	DET
fcis-2135	176	31	idea	idea	NOUN
fcis-2135	176	32	of	of	ADP
fcis-2135	176	33	confrontation	confrontation	NOUN
fcis-2135	176	34	into	into	ADP
fcis-2135	176	35	the	the	DET
fcis-2135	176	36	task	task	NOUN
fcis-2135	176	37	of	of	ADP
fcis-2135	176	38	pedestrian	pedestrian	NOUN
fcis-2135	176	39	trajectory	trajectory	NOUN
fcis-2135	176	40	prediction	prediction	NOUN
fcis-2135	176	41	by	by	ADP
fcis-2135	176	42	combining	combine	VERB
fcis-2135	176	43	sequence	sequence	NOUN
fcis-2135	176	44	prediction	prediction	NOUN
fcis-2135	176	45	model	model	NOUN
fcis-2135	176	46	and	and	CCONJ
fcis-2135	176	47	gan	gan	PROPN
fcis-2135	176	48	network	network	NOUN
fcis-2135	176	49	,	,	PUNCT
fcis-2135	176	50	showing	show	VERB
fcis-2135	176	51	the	the	DET
fcis-2135	176	52	sample	sample	NOUN
fcis-2135	176	53	space	space	NOUN
fcis-2135	176	54	of	of	ADP
fcis-2135	176	55	all	all	DET
fcis-2135	176	56	possible	possible	ADJ
fcis-2135	176	57	solutions	solution	NOUN
fcis-2135	176	58	.	.	PUNCT
fcis-2135	177	1	the	the	DET
fcis-2135	177	2	application	application	NOUN
fcis-2135	177	3	of	of	ADP
fcis-2135	177	4	gan	gan	PROPN
fcis-2135	177	5	network	network	NOUN
fcis-2135	177	6	overcomes	overcome	VERB
fcis-2135	177	7	the	the	DET
fcis-2135	177	8	shortcomings	shortcoming	NOUN
fcis-2135	177	9	of	of	ADP
fcis-2135	177	10	most	most	ADJ
fcis-2135	177	11	previous	previous	ADJ
fcis-2135	177	12	methods	method	NOUN
fcis-2135	177	13	based	base	VERB
fcis-2135	177	14	on	on	ADP
fcis-2135	177	15	optimizing	optimize	VERB
fcis-2135	177	16	the	the	DET
fcis-2135	177	17	distance	distance	NOUN
fcis-2135	177	18	between	between	ADP
fcis-2135	177	19	pedestrians	pedestrian	NOUN
fcis-2135	177	20	and	and	CCONJ
fcis-2135	177	21	predicting	predict	VERB
fcis-2135	177	22	only	only	ADV
fcis-2135	177	23	one	one	NUM
fcis-2135	177	24	trajectory	trajectory	NOUN
fcis-2135	177	25	.	.	PUNCT
fcis-2135	178	1	in	in	ADP
fcis-2135	178	2	the	the	DET
fcis-2135	178	3	process	process	NOUN
fcis-2135	178	4	of	of	ADP
fcis-2135	178	5	generating	generate	VERB
fcis-2135	178	6	discrimination	discrimination	NOUN
fcis-2135	178	7	,	,	PUNCT
fcis-2135	178	8	the	the	DET
fcis-2135	178	9	gan	gan	PROPN
fcis-2135	178	10	network	network	NOUN
fcis-2135	178	11	is	be	AUX
fcis-2135	178	12	prone	prone	ADJ
fcis-2135	178	13	to	to	ADP
fcis-2135	178	14	non	non	ADJ
fcis-2135	178	15	-	-	ADJ
fcis-2135	178	16	differentiable	differentiable	ADJ
fcis-2135	178	17	operations	operation	NOUN
fcis-2135	178	18	.	.	PUNCT
fcis-2135	179	1	in	in	ADP
fcis-2135	179	2	order	order	NOUN
fcis-2135	179	3	to	to	PART
fcis-2135	179	4	overcome	overcome	VERB
fcis-2135	179	5	this	this	DET
fcis-2135	179	6	limitation	limitation	NOUN
fcis-2135	179	7	,	,	PUNCT
fcis-2135	179	8	s	s	X
fcis-2135	179	9	-	-	PUNCT
fcis-2135	179	10	gan	gan	PROPN
fcis-2135	179	11	extends	extend	VERB
fcis-2135	179	12	social	social	ADJ
fcis-2135	179	13	pooling	pooling	NOUN
fcis-2135	179	14	into	into	ADP
fcis-2135	179	15	a	a	DET
fcis-2135	179	16	multi	multi	ADJ
fcis-2135	179	17	-	-	ADJ
fcis-2135	179	18	layer	layer	ADJ
fcis-2135	179	19	perceptron	perceptron	PROPN
fcis-2135	179	20	network	network	PROPN
fcis-2135	179	21	,	,	PUNCT
fcis-2135	179	22	predicting	predict	VERB
fcis-2135	179	23	multiple	multiple	ADJ
fcis-2135	179	24	socially	socially	ADV
fcis-2135	179	25	acceptable	acceptable	ADJ
fcis-2135	179	26	trajectories	trajectory	NOUN
fcis-2135	179	27	for	for	ADP
fcis-2135	179	28	pedestrians	pedestrian	NOUN
fcis-2135	179	29	.	.	PUNCT
fcis-2135	180	1	however	however	ADV
fcis-2135	180	2	,	,	PUNCT
fcis-2135	180	3	s	s	X
fcis-2135	180	4	-	-	PUNCT
fcis-2135	180	5	gan	gan	ADJ
fcis-2135	180	6	is	be	AUX
fcis-2135	180	7	not	not	PART
fcis-2135	180	8	only	only	ADV
fcis-2135	180	9	simple	simple	ADJ
fcis-2135	180	10	in	in	ADP
fcis-2135	180	11	modeling	model	VERB
fcis-2135	180	12	pedestrian	pedestrian	NOUN
fcis-2135	180	13	interaction	interaction	NOUN
fcis-2135	180	14	,	,	PUNCT
fcis-2135	180	15	but	but	CCONJ
fcis-2135	180	16	also	also	ADV
fcis-2135	180	17	does	do	AUX
fcis-2135	180	18	not	not	PART
fcis-2135	180	19	make	make	VERB
fcis-2135	180	20	full	full	ADJ
fcis-2135	180	21	use	use	NOUN
fcis-2135	180	22	of	of	ADP
fcis-2135	180	23	the	the	DET
fcis-2135	180	24	deep	deep	ADJ
fcis-2135	180	25	interaction	interaction	NOUN
fcis-2135	180	26	information	information	NOUN
fcis-2135	180	27	of	of	ADP
fcis-2135	180	28	pedestrians	pedestrian	NOUN
fcis-2135	180	29	.	.	PUNCT
fcis-2135	181	1	to	to	ADP
fcis-2135	181	2	this	this	DET
fcis-2135	181	3	end	end	NOUN
fcis-2135	181	4	,	,	PUNCT
fcis-2135	181	5	the	the	DET
fcis-2135	181	6	subsequent	subsequent	ADJ
fcis-2135	181	7	methods	method	NOUN
fcis-2135	181	8	explore	explore	VERB
fcis-2135	181	9	the	the	DET
fcis-2135	181	10	influencing	influence	VERB
fcis-2135	181	11	factors	factor	NOUN
fcis-2135	181	12	of	of	ADP
fcis-2135	181	13	pedestrian	pedestrian	NOUN
fcis-2135	181	14	trajectory	trajectory	NOUN
fcis-2135	181	15	by	by	ADP
fcis-2135	181	16	using	use	VERB
fcis-2135	181	17	attention	attention	NOUN
fcis-2135	181	18	mechanism	mechanism	NOUN
fcis-2135	181	19	[	[	X
fcis-2135	181	20	13,49	13,49	NUM
fcis-2135	181	21	-	-	SYM
fcis-2135	181	22	51	51	NUM
fcis-2135	181	23	]	]	PUNCT
fcis-2135	181	24	,	,	PUNCT
fcis-2135	181	25	increasing	increase	VERB
fcis-2135	181	26	scene	scene	NOUN
fcis-2135	181	27	interaction	interaction	NOUN
fcis-2135	182	1	[	[	X
fcis-2135	182	2	13,5254	13,5254	NUM
fcis-2135	182	3	]	]	X
fcis-2135	182	4	,	,	PUNCT
fcis-2135	182	5	feasibility	feasibility	NOUN
fcis-2135	182	6	constraints	constraint	NOUN
fcis-2135	182	7	[	[	X
fcis-2135	182	8	46	46	NUM
fcis-2135	182	9	]	]	PUNCT
fcis-2135	182	10	,	,	PUNCT
fcis-2135	182	11	etc	etc	X
fcis-2135	182	12	.	.	X
fcis-2135	182	13	s	s	X
fcis-2135	182	14	-	-	PUNCT
fcis-2135	182	15	gan	gin	VERB
fcis-2135	182	16	and	and	CCONJ
fcis-2135	182	17	sophie	sophie	NOUN
fcis-2135	182	18	are	be	AUX
fcis-2135	182	19	single	single	ADJ
fcis-2135	182	20	behavior	behavior	NOUN
fcis-2135	182	21	patterns	pattern	NOUN
fcis-2135	182	22	with	with	ADP
fcis-2135	182	23	high	high	ADJ
fcis-2135	182	24	variance	variance	NOUN
fcis-2135	182	25	,	,	PUNCT
fcis-2135	182	26	which	which	PRON
fcis-2135	182	27	are	be	AUX
fcis-2135	182	28	limited	limit	VERB
fcis-2135	182	29	by	by	ADP
fcis-2135	182	30	social	social	ADJ
fcis-2135	182	31	behavior	behavior	NOUN
fcis-2135	182	32	and	and	CCONJ
fcis-2135	182	33	can	can	AUX
fcis-2135	182	34	not	not	PART
fcis-2135	182	35	learn	learn	VERB
fcis-2135	182	36	the	the	DET
fcis-2135	182	37	real	real	ADJ
fcis-2135	182	38	multimodal	multimodal	ADJ
fcis-2135	182	39	distribution	distribution	NOUN
fcis-2135	182	40	of	of	ADP
fcis-2135	182	41	pedestrians	pedestrian	NOUN
fcis-2135	182	42	.	.	PUNCT
fcis-2135	183	1	to	to	ADP
fcis-2135	183	2	this	this	DET
fcis-2135	183	3	end	end	NOUN
fcis-2135	183	4	,	,	PUNCT
fcis-2135	183	5	a	a	DET
fcis-2135	183	6	graph	graph	NOUN
fcis-2135	183	7	-	-	PUNCT
fcis-2135	183	8	based	base	VERB
fcis-2135	183	9	generative	generative	ADJ
fcis-2135	183	10	adversarial	adversarial	ADJ
fcis-2135	183	11	network	network	NOUN
fcis-2135	183	12	social	social	ADJ
fcis-2135	183	13	-	-	PUNCT
fcis-2135	183	14	bigat[51	bigat[51	PROPN
fcis-2135	183	15	]	]	PUNCT
fcis-2135	183	16	was	be	AUX
fcis-2135	183	17	proposed	propose	VERB
fcis-2135	183	18	to	to	PART
fcis-2135	183	19	construct	construct	VERB
fcis-2135	183	20	a	a	DET
fcis-2135	183	21	generative	generative	ADJ
fcis-2135	183	22	model	model	NOUN
fcis-2135	183	23	for	for	ADP
fcis-2135	183	24	learning	learn	VERB
fcis-2135	183	25	multimodal	multimodal	ADJ
fcis-2135	183	26	trajectory	trajectory	NOUN
fcis-2135	183	27	distributions	distribution	NOUN
fcis-2135	183	28	.	.	PUNCT
fcis-2135	184	1	since	since	SCONJ
fcis-2135	184	2	the	the	DET
fcis-2135	184	3	gan	gan	PROPN
fcis-2135	184	4	network	network	NOUN
fcis-2135	184	5	is	be	AUX
fcis-2135	184	6	prone	prone	ADJ
fcis-2135	184	7	to	to	PART
fcis-2135	184	8	mode	mode	VERB
fcis-2135	184	9	collapse	collapse	NOUN
fcis-2135	184	10	and	and	CCONJ
fcis-2135	184	11	fall	fall	NOUN
fcis-2135	184	12	,	,	PUNCT
fcis-2135	184	13	info	info	NOUN
fcis-2135	184	14	-	-	PUNCT
fcis-2135	184	15	gan	gan	NOUN
fcis-2135	184	16	in	in	ADP
fcis-2135	184	17	social	social	ADJ
fcis-2135	184	18	ways	way	NOUN
fcis-2135	184	19	[	[	X
fcis-2135	184	20	55	55	NUM
fcis-2135	184	21	]	]	PUNCT
fcis-2135	184	22	can	can	AUX
fcis-2135	184	23	better	well	ADV
fcis-2135	184	24	improve	improve	VERB
fcis-2135	184	25	multimodal	multimodal	ADJ
fcis-2135	184	26	pedestrian	pedestrian	NOUN
fcis-2135	184	27	trajectory	trajectory	NOUN
fcis-2135	184	28	prediction	prediction	NOUN
fcis-2135	184	29	and	and	CCONJ
fcis-2135	184	30	avoid	avoid	VERB
fcis-2135	184	31	these	these	DET
fcis-2135	184	32	problems	problem	NOUN
fcis-2135	184	33	.	.	PUNCT
fcis-2135	185	1	gan	gin	VERB
fcis-2135	185	2	-	-	PUNCT
fcis-2135	185	3	based	base	VERB
fcis-2135	185	4	methods	method	NOUN
fcis-2135	185	5	usually	usually	ADV
fcis-2135	185	6	deal	deal	VERB
fcis-2135	185	7	with	with	ADP
fcis-2135	185	8	future	future	ADJ
fcis-2135	185	9	uncertainty	uncertainty	NOUN
fcis-2135	185	10	by	by	ADP
fcis-2135	185	11	sampling	sample	VERB
fcis-2135	185	12	a	a	DET
fcis-2135	185	13	latent	latent	NOUN
fcis-2135	185	14	variable	variable	NOUN
fcis-2135	185	15	.	.	PUNCT
fcis-2135	186	1	previous	previous	ADJ
fcis-2135	186	2	studies	study	NOUN
fcis-2135	186	3	have	have	AUX
fcis-2135	186	4	rarely	rarely	ADV
fcis-2135	186	5	discussed	discuss	VERB
fcis-2135	186	6	these	these	DET
fcis-2135	186	7	latent	latent	NOUN
fcis-2135	186	8	variables	variable	NOUN
fcis-2135	186	9	in	in	ADP
fcis-2135	186	10	depth	depth	NOUN
fcis-2135	186	11	.	.	PUNCT
fcis-2135	187	1	tppo	tppo	X
fcis-2135	187	2	[	[	X
fcis-2135	187	3	56	56	NUM
fcis-2135	187	4	]	]	PUNCT
fcis-2135	187	5	designed	design	VERB
fcis-2135	187	6	a	a	DET
fcis-2135	187	7	latent	latent	ADJ
fcis-2135	187	8	variable	variable	ADJ
fcis-2135	187	9	prediction	prediction	NOUN
fcis-2135	187	10	model	model	NOUN
fcis-2135	187	11	to	to	PART
fcis-2135	187	12	estimate	estimate	VERB
fcis-2135	187	13	the	the	DET
fcis-2135	187	14	distribution	distribution	NOUN
fcis-2135	187	15	of	of	ADP
fcis-2135	187	16	latent	latent	NOUN
fcis-2135	187	17	variables	variable	NOUN
fcis-2135	187	18	from	from	ADP
fcis-2135	187	19	observations	observation	NOUN
fcis-2135	187	20	and	and	CCONJ
fcis-2135	187	21	real	real	ADJ
fcis-2135	187	22	trajectories	trajectory	NOUN
fcis-2135	187	23	,	,	PUNCT
fcis-2135	187	24	and	and	CCONJ
fcis-2135	187	25	achieved	achieve	VERB
fcis-2135	187	26	excellent	excellent	ADJ
fcis-2135	187	27	prediction	prediction	NOUN
fcis-2135	187	28	performance	performance	NOUN
fcis-2135	187	29	.	.	PUNCT
fcis-2135	188	1	the	the	DET
fcis-2135	188	2	pedestrian	pedestrian	PROPN
fcis-2135	188	3	trajectory	trajectory	NOUN
fcis-2135	188	4	prediction	prediction	NOUN
fcis-2135	188	5	method	method	NOUN
fcis-2135	188	6	proposed	propose	VERB
fcis-2135	188	7	above	above	ADV
fcis-2135	188	8	is	be	AUX
fcis-2135	188	9	mainly	mainly	ADV
fcis-2135	188	10	to	to	PART
fcis-2135	188	11	learn	learn	VERB
fcis-2135	188	12	and	and	CCONJ
fcis-2135	188	13	predict	predict	VERB
fcis-2135	188	14	in	in	ADP
fcis-2135	188	15	two	two	NUM
fcis-2135	188	16	-	-	PUNCT
fcis-2135	188	17	dimensional	dimensional	ADJ
fcis-2135	188	18	image	image	NOUN
fcis-2135	188	19	space	space	NOUN
fcis-2135	188	20	.	.	PUNCT
fcis-2135	189	1	since	since	SCONJ
fcis-2135	189	2	human	human	ADJ
fcis-2135	189	3	motion	motion	NOUN
fcis-2135	189	4	occurs	occur	VERB
fcis-2135	189	5	in	in	ADP
fcis-2135	189	6	the	the	DET
fcis-2135	189	7	three	three	NUM
fcis-2135	189	8	-	-	PUNCT
fcis-2135	189	9	dimensional	dimensional	ADJ
fcis-2135	189	10	world	world	NOUN
fcis-2135	189	11	,	,	PUNCT
fcis-2135	189	12	experiments	experiment	NOUN
fcis-2135	189	13	prove	prove	VERB
fcis-2135	189	14	that	that	SCONJ
fcis-2135	189	15	[	[	X
fcis-2135	189	16	57	57	NUM
fcis-2135	189	17	]	]	PUNCT
fcis-2135	189	18	is	be	AUX
fcis-2135	189	19	more	more	ADV
fcis-2135	189	20	effective	effective	ADJ
fcis-2135	189	21	in	in	ADP
fcis-2135	189	22	learning	learn	VERB
fcis-2135	189	23	and	and	CCONJ
fcis-2135	189	24	predicting	predict	VERB
fcis-2135	189	25	pedestrian	pedestrian	NOUN
fcis-2135	189	26	trajectories	trajectory	NOUN
fcis-2135	189	27	in	in	ADP
fcis-2135	189	28	three	three	NUM
fcis-2135	189	29	-	-	PUNCT
fcis-2135	189	30	dimensional	dimensional	ADJ
fcis-2135	189	31	space	space	NOUN
fcis-2135	189	32	,	,	PUNCT
fcis-2135	189	33	which	which	PRON
fcis-2135	189	34	also	also	ADV
fcis-2135	189	35	provides	provide	VERB
fcis-2135	189	36	a	a	DET
fcis-2135	189	37	new	new	ADJ
fcis-2135	189	38	direction	direction	NOUN
fcis-2135	189	39	for	for	ADP
fcis-2135	189	40	the	the	DET
fcis-2135	189	41	promotion	promotion	NOUN
fcis-2135	189	42	and	and	CCONJ
fcis-2135	189	43	application	application	NOUN
fcis-2135	189	44	of	of	ADP
fcis-2135	189	45	gan	gan	ADJ
fcis-2135	189	46	network	network	NOUN
fcis-2135	189	47	in	in	ADP
fcis-2135	189	48	the	the	DET
fcis-2135	189	49	field	field	NOUN
fcis-2135	189	50	of	of	ADP
fcis-2135	189	51	trajectory	trajectory	NOUN
fcis-2135	189	52	prediction	prediction	NOUN
fcis-2135	189	53	.	.	PUNCT
fcis-2135	190	1	the	the	DET
fcis-2135	190	2	comparison	comparison	NOUN
fcis-2135	190	3	of	of	ADP
fcis-2135	190	4	pedestrian	pedestrian	NOUN
fcis-2135	190	5	trajectory	trajectory	NOUN
fcis-2135	190	6	prediction	prediction	NOUN
fcis-2135	190	7	methods	method	NOUN
fcis-2135	190	8	based	base	VERB
fcis-2135	190	9	on	on	ADP
fcis-2135	190	10	gan	gan	PROPN
fcis-2135	190	11	is	be	AUX
fcis-2135	190	12	shown	show	VERB
fcis-2135	190	13	in	in	ADP
fcis-2135	190	14	table	table	NOUN
fcis-2135	190	15	2	2	NUM
fcis-2135	190	16	.	.	X
fcis-2135	190	17	l2	l2	NOUN
fcis-2135	190	18	is	be	AUX
fcis-2135	190	19	the	the	DET
fcis-2135	190	20	least	least	ADJ
fcis-2135	190	21	square	square	ADJ
fcis-2135	190	22	error	error	NOUN
fcis-2135	190	23	and	and	CCONJ
fcis-2135	190	24	kl	kl	PROPN
fcis-2135	190	25	is	be	AUX
fcis-2135	190	26	the	the	DET
fcis-2135	190	27	relative	relative	ADJ
fcis-2135	190	28	entropy	entropy	PROPN
fcis-2135	190	29	.	.	PUNCT
fcis-2135	191	1	table	table	NOUN
fcis-2135	191	2	2	2	NUM
fcis-2135	191	3	.	.	PUNCT
fcis-2135	191	4	comparison	comparison	NOUN
fcis-2135	191	5	of	of	ADP
fcis-2135	191	6	pedestrian	pedestrian	NOUN
fcis-2135	191	7	trajectory	trajectory	NOUN
fcis-2135	191	8	prediction	prediction	NOUN
fcis-2135	191	9	methods	method	NOUN
fcis-2135	191	10	based	base	VERB
fcis-2135	191	11	on	on	ADP
fcis-2135	191	12	gan	gan	PROPN
fcis-2135	191	13	method	method	NOUN
fcis-2135	191	14	advantage	advantage	NOUN
fcis-2135	191	15	shortcoming	shortcoming	NOUN
fcis-2135	191	16	research	research	NOUN
fcis-2135	191	17	direction	direction	NOUN
fcis-2135	191	18	loss	loss	NOUN
fcis-2135	191	19	function	function	NOUN
fcis-2135	191	20	sophie[13	sophie[13	NOUN
fcis-2135	191	21	]	]	PUNCT
fcis-2135	191	22	semantic	semantic	ADJ
fcis-2135	191	23	scenario	scenario	NOUN
fcis-2135	191	24	manual	manual	NOUN
fcis-2135	191	25	sorting	sort	VERB
fcis-2135	191	26	flexible	flexible	ADJ
fcis-2135	191	27	performance	performance	NOUN
fcis-2135	191	28	l2+confrontation	l2+confrontation	NOUN
fcis-2135	191	29	s	s	NOUN
fcis-2135	191	30	-	-	PUNCT
fcis-2135	191	31	gan	gin	VERB
fcis-2135	192	1	[	[	X
fcis-2135	192	2	28	28	NUM
fcis-2135	192	3	]	]	X
fcis-2135	192	4	reasonable	reasonable	ADJ
fcis-2135	192	5	and	and	CCONJ
fcis-2135	192	6	diverse	diverse	ADJ
fcis-2135	192	7	slow	slow	ADJ
fcis-2135	192	8	sampling	sample	VERB
fcis-2135	192	9	enrichment	enrichment	NOUN
fcis-2135	192	10	mode	mode	NOUN
fcis-2135	192	11	l2+confrontation	l2+confrontation	NOUN
fcis-2135	192	12	gcans	gcan	NOUN
fcis-2135	193	1	[	[	X
fcis-2135	193	2	46	46	NUM
fcis-2135	193	3	]	]	SYM
fcis-2135	193	4	probability	probability	NOUN
fcis-2135	193	5	distribution	distribution	NOUN
fcis-2135	193	6	complex	complex	NOUN
fcis-2135	193	7	and	and	CCONJ
fcis-2135	193	8	changeable	changeable	ADJ
fcis-2135	193	9	wide	wide	ADJ
fcis-2135	193	10	application	application	NOUN
fcis-2135	193	11	type	type	NOUN
fcis-2135	193	12	reconstruction+confrontation+kl	reconstruction+confrontation+kl	NOUN
fcis-2135	193	13	zhiyuan	zhiyuan	PROPN
fcis-2135	193	14	zhang	zhang	PROPN
fcis-2135	194	1	[	[	X
fcis-2135	194	2	49	49	NUM
fcis-2135	194	3	]	]	X
fcis-2135	194	4	rich	rich	ADJ
fcis-2135	194	5	features	feature	VERB
fcis-2135	194	6	insufficient	insufficient	ADJ
fcis-2135	194	7	generalization	generalization	NOUN
fcis-2135	194	8	scene	scene	NOUN
fcis-2135	194	9	interaction	interaction	NOUN
fcis-2135	194	10	l2+confrontation	l2+confrontation	PROPN
fcis-2135	194	11	yasheng	yasheng	PROPN
fcis-2135	194	12	sun	sun	PROPN
fcis-2135	195	1	[	[	X
fcis-2135	195	2	50	50	NUM
fcis-2135	195	3	]	]	PUNCT
fcis-2135	195	4	social	social	ADJ
fcis-2135	195	5	attention	attention	NOUN
fcis-2135	195	6	time	time	NOUN
fcis-2135	195	7	cost	cost	NOUN
fcis-2135	195	8	information	information	NOUN
fcis-2135	195	9	fusion	fusion	NOUN
fcis-2135	195	10	l2+confrontation	l2+confrontation	PROPN
fcis-2135	195	11	stg	stg	PROPN
fcis-2135	195	12	-	-	PUNCT
fcis-2135	195	13	gan	gan	NOUN
fcis-2135	195	14	[	[	PUNCT
fcis-2135	195	15	52	52	NUM
fcis-2135	195	16	]	]	X
fcis-2135	195	17	global	global	ADJ
fcis-2135	195	18	interaction	interaction	NOUN
fcis-2135	195	19	inter	inter	NOUN
fcis-2135	195	20	graph	graph	NOUN
fcis-2135	195	21	disassociation	disassociation	NOUN
fcis-2135	195	22	optimize	optimize	NOUN
fcis-2135	195	23	and	and	CCONJ
fcis-2135	195	24	expand	expand	VERB
fcis-2135	195	25	l2+confrontation	l2+confrontation	NOUN
fcis-2135	195	26	sun	sun	NOUN
fcis-2135	195	27	[	[	X
fcis-2135	195	28	54	54	NUM
fcis-2135	195	29	]	]	PUNCT
fcis-2135	195	30	reciprocal	reciprocal	ADJ
fcis-2135	195	31	constraint	constraint	NOUN
fcis-2135	195	32	slow	slow	ADJ
fcis-2135	195	33	fitting	fitting	ADJ
fcis-2135	195	34	application	application	NOUN
fcis-2135	195	35	promotion	promotion	NOUN
fcis-2135	195	36	confrontation+reciprocity	confrontation+reciprocity	PROPN
fcis-2135	195	37	social	social	ADJ
fcis-2135	195	38	ways	way	NOUN
fcis-2135	195	39	[	[	X
fcis-2135	195	40	55	55	NUM
fcis-2135	195	41	]	]	PUNCT
fcis-2135	195	42	multimode	multimode	ADJ
fcis-2135	195	43	distribution	distribution	NOUN
fcis-2135	195	44	application	application	NOUN
fcis-2135	195	45	restrictions	restriction	NOUN
fcis-2135	195	46	decision	decision	NOUN
fcis-2135	195	47	optimization	optimization	NOUN
fcis-2135	195	48	countermeasure+information	countermeasure+information	NOUN
fcis-2135	195	49	tppo	tppo	NOUN
fcis-2135	195	50	[	[	X
fcis-2135	195	51	56	56	NUM
fcis-2135	195	52	]	]	PUNCT
fcis-2135	195	53	potential	potential	ADJ
fcis-2135	195	54	variables	variable	NOUN
fcis-2135	195	55	poor	poor	ADJ
fcis-2135	195	56	reliability	reliability	NOUN
fcis-2135	195	57	improve	improve	VERB
fcis-2135	195	58	control	control	NOUN
fcis-2135	195	59	l2+confrontation+kl	l2+confrontation+kl	PROPN
fcis-2135	195	60	zhong	zhong	PROPN
fcis-2135	196	1	[	[	X
fcis-2135	196	2	57	57	NUM
fcis-2135	196	3	]	]	PUNCT
fcis-2135	196	4	3d	3d	NUM
fcis-2135	196	5	space	space	NOUN
fcis-2135	196	6	high	high	PROPN
fcis-2135	196	7	complexity	complexity	NOUN
fcis-2135	196	8	generalization	generalization	NOUN
fcis-2135	196	9	performance	performance	NOUN
fcis-2135	196	10	l2+confrontation	l2+confrontation	NOUN
fcis-2135	196	11	3.2.3	3.2.3	NUM
fcis-2135	196	12	.	.	PUNCT
fcis-2135	197	1	prediction	prediction	NOUN
fcis-2135	197	2	method	method	NOUN
fcis-2135	197	3	based	base	VERB
fcis-2135	197	4	on	on	ADP
fcis-2135	197	5	gcn	gcn	NOUN
fcis-2135	197	6	(	(	PUNCT
fcis-2135	197	7	1	1	NUM
fcis-2135	197	8	)	)	PUNCT
fcis-2135	197	9	trajectory	trajectory	NOUN
fcis-2135	197	10	prediction	prediction	NOUN
fcis-2135	197	11	based	base	VERB
fcis-2135	197	12	on	on	ADP
fcis-2135	197	13	space	space	NOUN
fcis-2135	197	14	-	-	PUNCT
fcis-2135	197	15	time	time	NOUN
fcis-2135	197	16	graph	graph	NOUN
fcis-2135	197	17	.	.	PUNCT
fcis-2135	198	1	based	base	VERB
fcis-2135	198	2	on	on	ADP
fcis-2135	198	3	the	the	DET
fcis-2135	198	4	wide	wide	ADJ
fcis-2135	198	5	application	application	NOUN
fcis-2135	198	6	of	of	ADP
fcis-2135	198	7	graph	graph	NOUN
fcis-2135	198	8	convolutional	convolutional	ADJ
fcis-2135	198	9	networks	network	NOUN
fcis-2135	198	10	in	in	ADP
fcis-2135	198	11	behavior	behavior	NOUN
fcis-2135	198	12	recognition	recognition	NOUN
fcis-2135	198	13	[	[	X
fcis-2135	198	14	58	58	NUM
fcis-2135	198	15	]	]	PUNCT
fcis-2135	198	16	,	,	PUNCT
fcis-2135	198	17	traffic	traffic	NOUN
fcis-2135	198	18	prediction	prediction	NOUN
fcis-2135	198	19	[	[	X
fcis-2135	198	20	59	59	NUM
fcis-2135	198	21	]	]	PUNCT
fcis-2135	198	22	,	,	PUNCT
fcis-2135	198	23	demand	demand	NOUN
fcis-2135	198	24	prediction	prediction	NOUN
fcis-2135	198	25	[	[	X
fcis-2135	198	26	60	60	NUM
fcis-2135	198	27	]	]	PUNCT
fcis-2135	198	28	,	,	PUNCT
fcis-2135	198	29	etc	etc	X
fcis-2135	198	30	.	.	X
fcis-2135	198	31	,	,	PUNCT
fcis-2135	198	32	many	many	ADJ
fcis-2135	198	33	studies	study	NOUN
fcis-2135	198	34	have	have	AUX
fcis-2135	198	35	tried	try	VERB
fcis-2135	198	36	to	to	PART
fcis-2135	198	37	apply	apply	VERB
fcis-2135	198	38	spatiotemporal	spatiotemporal	ADJ
fcis-2135	198	39	graphs	graph	NOUN
fcis-2135	198	40	[	[	PUNCT
fcis-2135	198	41	61,52,60	61,52,60	NUM
fcis-2135	198	42	-	-	SYM
fcis-2135	198	43	65	65	NUM
fcis-2135	198	44	]	]	PUNCT
fcis-2135	198	45	to	to	ADP
fcis-2135	198	46	pedestrian	pedestrian	NOUN
fcis-2135	198	47	trajectory	trajectory	NOUN
fcis-2135	198	48	prediction	prediction	NOUN
fcis-2135	198	49	tasks	task	NOUN
fcis-2135	198	50	and	and	CCONJ
fcis-2135	198	51	achieved	achieve	VERB
fcis-2135	198	52	good	good	ADJ
fcis-2135	198	53	prediction	prediction	NOUN
fcis-2135	198	54	performance	performance	NOUN
fcis-2135	198	55	.	.	PUNCT
fcis-2135	199	1	73	73	NUM
fcis-2135	200	1	the	the	DET
fcis-2135	200	2	spatio	spatio	PROPN
fcis-2135	200	3	-	-	PUNCT
fcis-2135	200	4	temporal	temporal	ADJ
fcis-2135	200	5	map	map	NOUN
fcis-2135	200	6	in	in	ADP
fcis-2135	200	7	the	the	DET
fcis-2135	200	8	prediction	prediction	NOUN
fcis-2135	200	9	task	task	NOUN
fcis-2135	200	10	can	can	AUX
fcis-2135	200	11	be	be	AUX
fcis-2135	200	12	divided	divide	VERB
fcis-2135	200	13	into	into	ADP
fcis-2135	200	14	two	two	NUM
fcis-2135	200	15	dimensions	dimension	NOUN
fcis-2135	200	16	:	:	PUNCT
fcis-2135	200	17	space	space	NOUN
fcis-2135	200	18	and	and	CCONJ
fcis-2135	200	19	time	time	NOUN
fcis-2135	200	20	.	.	PUNCT
fcis-2135	201	1	the	the	DET
fcis-2135	201	2	space	space	NOUN
fcis-2135	201	3	dimension	dimension	NOUN
fcis-2135	201	4	models	model	VERB
fcis-2135	201	5	the	the	DET
fcis-2135	201	6	interaction	interaction	NOUN
fcis-2135	201	7	between	between	ADP
fcis-2135	201	8	the	the	DET
fcis-2135	201	9	target	target	NOUN
fcis-2135	201	10	pedestrian	pedestrian	NOUN
fcis-2135	201	11	and	and	CCONJ
fcis-2135	201	12	its	its	PRON
fcis-2135	201	13	neighbors	neighbor	NOUN
fcis-2135	201	14	,	,	PUNCT
fcis-2135	201	15	while	while	SCONJ
fcis-2135	201	16	the	the	DET
fcis-2135	201	17	time	time	NOUN
fcis-2135	201	18	dimension	dimension	NOUN
fcis-2135	201	19	models	model	NOUN
fcis-2135	201	20	the	the	DET
fcis-2135	201	21	historical	historical	ADJ
fcis-2135	201	22	trajectory	trajectory	NOUN
fcis-2135	201	23	of	of	ADP
fcis-2135	201	24	the	the	DET
fcis-2135	201	25	pedestrian	pedestrian	NOUN
fcis-2135	201	26	.	.	PUNCT
fcis-2135	202	1	some	some	DET
fcis-2135	202	2	methods	method	NOUN
fcis-2135	202	3	are	be	AUX
fcis-2135	202	4	extended	extend	VERB
fcis-2135	202	5	on	on	ADP
fcis-2135	202	6	this	this	DET
fcis-2135	202	7	basis	basis	NOUN
fcis-2135	202	8	.	.	PUNCT
fcis-2135	203	1	for	for	ADP
fcis-2135	203	2	example	example	NOUN
fcis-2135	203	3	,	,	PUNCT
fcis-2135	203	4	recursive	recursive	ADJ
fcis-2135	203	5	social	social	ADJ
fcis-2135	203	6	behavior	behavior	NOUN
fcis-2135	203	7	graph	graph	NOUN
fcis-2135	203	8	[	[	X
fcis-2135	203	9	25	25	NUM
fcis-2135	203	10	]	]	PUNCT
fcis-2135	203	11	recursively	recursively	ADV
fcis-2135	203	12	updates	update	VERB
fcis-2135	203	13	individual	individual	ADJ
fcis-2135	203	14	features	feature	NOUN
fcis-2135	203	15	within	within	ADP
fcis-2135	203	16	the	the	DET
fcis-2135	203	17	interaction	interaction	NOUN
fcis-2135	203	18	range	range	NOUN
fcis-2135	203	19	to	to	PART
fcis-2135	203	20	enhance	enhance	VERB
fcis-2135	203	21	the	the	DET
fcis-2135	203	22	interaction	interaction	NOUN
fcis-2135	203	23	relationship	relationship	NOUN
fcis-2135	203	24	.	.	PUNCT
fcis-2135	204	1	zhang	zhang	PROPN
fcis-2135	204	2	et	et	PROPN
fcis-2135	204	3	al	al	PROPN
fcis-2135	204	4	.	.	PUNCT
fcis-2135	205	1	[	[	X
fcis-2135	205	2	22	22	NUM
fcis-2135	205	3	]	]	PUNCT
fcis-2135	205	4	dynamically	dynamically	ADV
fcis-2135	205	5	constructed	construct	VERB
fcis-2135	205	6	a	a	DET
fcis-2135	205	7	directed	direct	VERB
fcis-2135	205	8	social	social	ADJ
fcis-2135	205	9	graph	graph	NOUN
fcis-2135	205	10	in	in	ADP
fcis-2135	205	11	the	the	DET
fcis-2135	205	12	direction	direction	NOUN
fcis-2135	205	13	of	of	ADP
fcis-2135	205	14	position	position	NOUN
fcis-2135	205	15	and	and	CCONJ
fcis-2135	205	16	speed	speed	NOUN
fcis-2135	205	17	to	to	PART
fcis-2135	205	18	effectively	effectively	ADV
fcis-2135	205	19	capture	capture	VERB
fcis-2135	205	20	the	the	DET
fcis-2135	205	21	interaction	interaction	NOUN
fcis-2135	205	22	behavior	behavior	NOUN
fcis-2135	205	23	of	of	ADP
fcis-2135	205	24	pedestrians	pedestrian	NOUN
fcis-2135	205	25	.	.	PUNCT
fcis-2135	206	1	star	star	NOUN
fcis-2135	207	1	[	[	X
fcis-2135	207	2	65	65	NUM
fcis-2135	207	3	]	]	X
fcis-2135	207	4	processed	process	VERB
fcis-2135	207	5	the	the	DET
fcis-2135	207	6	spatio	spatio	NOUN
fcis-2135	207	7	-	-	PUNCT
fcis-2135	207	8	temporal	temporal	ADJ
fcis-2135	207	9	modeling	modeling	NOUN
fcis-2135	207	10	of	of	ADP
fcis-2135	207	11	graphs	graph	NOUN
fcis-2135	207	12	based	base	VERB
fcis-2135	207	13	on	on	ADP
fcis-2135	207	14	the	the	DET
fcis-2135	207	15	enhanced	enhanced	ADJ
fcis-2135	207	16	attention	attention	NOUN
fcis-2135	207	17	mechanism	mechanism	NOUN
fcis-2135	207	18	of	of	ADP
fcis-2135	207	19	transformer	transformer	ADJ
fcis-2135	207	20	structure	structure	NOUN
fcis-2135	207	21	.	.	PUNCT
fcis-2135	208	1	liang	liang	PROPN
fcis-2135	208	2	et	et	PROPN
fcis-2135	208	3	al	al	PROPN
fcis-2135	208	4	.	.	PUNCT
fcis-2135	209	1	[	[	X
fcis-2135	209	2	24	24	NUM
fcis-2135	209	3	]	]	PUNCT
fcis-2135	209	4	designed	design	VERB
fcis-2135	209	5	rnn	rnn	NOUN
fcis-2135	209	6	on	on	ADP
fcis-2135	209	7	the	the	DET
fcis-2135	209	8	spatial	spatial	ADJ
fcis-2135	209	9	graph	graph	NOUN
fcis-2135	209	10	to	to	PART
fcis-2135	209	11	encode	encode	VERB
fcis-2135	209	12	the	the	DET
fcis-2135	209	13	inductive	inductive	ADJ
fcis-2135	209	14	bias	bias	NOUN
fcis-2135	209	15	of	of	ADP
fcis-2135	209	16	pedestrian	pedestrian	NOUN
fcis-2135	209	17	motion	motion	NOUN
fcis-2135	209	18	patterns	pattern	NOUN
fcis-2135	209	19	.	.	PUNCT
fcis-2135	210	1	however	however	ADV
fcis-2135	210	2	,	,	PUNCT
fcis-2135	210	3	these	these	DET
fcis-2135	210	4	graph	graph	NOUN
fcis-2135	210	5	network	network	NOUN
fcis-2135	210	6	-	-	PUNCT
fcis-2135	210	7	based	base	VERB
fcis-2135	210	8	prediction	prediction	NOUN
fcis-2135	210	9	methods	method	NOUN
fcis-2135	210	10	do	do	AUX
fcis-2135	210	11	not	not	PART
fcis-2135	210	12	have	have	VERB
fcis-2135	210	13	multimodal	multimodal	NOUN
fcis-2135	210	14	modeling	model	VERB
fcis-2135	210	15	capabilities	capability	NOUN
fcis-2135	210	16	.	.	PUNCT
fcis-2135	211	1	for	for	ADP
fcis-2135	211	2	this	this	DET
fcis-2135	211	3	reason	reason	NOUN
fcis-2135	211	4	,	,	PUNCT
fcis-2135	211	5	ivanovic	ivanovic	PROPN
fcis-2135	211	6	et	et	PROPN
fcis-2135	211	7	al	al	PROPN
fcis-2135	211	8	.	.	PUNCT
fcis-2135	212	1	[	[	X
fcis-2135	212	2	61	61	NUM
fcis-2135	212	3	]	]	PUNCT
fcis-2135	212	4	demonstrated	demonstrate	VERB
fcis-2135	212	5	a	a	DET
fcis-2135	212	6	highly	highly	ADV
fcis-2135	212	7	multimodal	multimodal	ADJ
fcis-2135	212	8	multi	multi	ADJ
fcis-2135	212	9	-	-	ADJ
fcis-2135	212	10	person	person	ADJ
fcis-2135	212	11	scenario	scenario	NOUN
fcis-2135	212	12	that	that	PRON
fcis-2135	212	13	guarantees	guarantee	VERB
fcis-2135	212	14	performance	performance	NOUN
fcis-2135	212	15	in	in	ADP
fcis-2135	212	16	trajectory	trajectory	NOUN
fcis-2135	212	17	prediction	prediction	NOUN
fcis-2135	212	18	modeling	modeling	NOUN
fcis-2135	212	19	.	.	PUNCT
fcis-2135	213	1	since	since	SCONJ
fcis-2135	213	2	these	these	DET
fcis-2135	213	3	methods	method	NOUN
fcis-2135	213	4	introduce	introduce	VERB
fcis-2135	213	5	a	a	DET
fcis-2135	213	6	graph	graph	NOUN
fcis-2135	213	7	at	at	ADP
fcis-2135	213	8	each	each	DET
fcis-2135	213	9	time	time	NOUN
fcis-2135	213	10	step	step	NOUN
fcis-2135	213	11	,	,	PUNCT
fcis-2135	213	12	they	they	PRON
fcis-2135	213	13	can	can	AUX
fcis-2135	213	14	handle	handle	VERB
fcis-2135	213	15	graphs	graph	NOUN
fcis-2135	213	16	that	that	PRON
fcis-2135	213	17	change	change	NOUN
fcis-2135	213	18	between	between	ADP
fcis-2135	213	19	prediction	prediction	NOUN
fcis-2135	213	20	steps	step	NOUN
fcis-2135	213	21	.	.	PUNCT
fcis-2135	214	1	however	however	ADV
fcis-2135	214	2	,	,	PUNCT
fcis-2135	214	3	this	this	PRON
fcis-2135	214	4	is	be	AUX
fcis-2135	214	5	only	only	ADV
fcis-2135	214	6	an	an	DET
fcis-2135	214	7	implicit	implicit	ADJ
fcis-2135	214	8	ability	ability	NOUN
fcis-2135	214	9	to	to	PART
fcis-2135	214	10	handle	handle	VERB
fcis-2135	214	11	dynamic	dynamic	ADJ
fcis-2135	214	12	edges	edge	NOUN
fcis-2135	214	13	and	and	CCONJ
fcis-2135	214	14	can	can	AUX
fcis-2135	214	15	not	not	PART
fcis-2135	214	16	explicitly	explicitly	ADV
fcis-2135	214	17	handle	handle	VERB
fcis-2135	214	18	dynamic	dynamic	ADJ
fcis-2135	214	19	nodes	node	NOUN
fcis-2135	214	20	and	and	CCONJ
fcis-2135	214	21	edges	edge	NOUN
fcis-2135	214	22	.	.	PUNCT
fcis-2135	215	1	(	(	PUNCT
fcis-2135	215	2	2	2	X
fcis-2135	215	3	)	)	PUNCT
fcis-2135	215	4	trajectory	trajectory	NOUN
fcis-2135	215	5	prediction	prediction	NOUN
fcis-2135	215	6	based	base	VERB
fcis-2135	215	7	on	on	ADP
fcis-2135	215	8	graph	graph	NOUN
fcis-2135	215	9	attention	attention	NOUN
fcis-2135	215	10	mechanism	mechanism	NOUN
fcis-2135	215	11	.	.	PUNCT
fcis-2135	216	1	pedestrian	pedestrian	NOUN
fcis-2135	216	2	trajectories	trajectory	NOUN
fcis-2135	216	3	are	be	AUX
fcis-2135	216	4	often	often	ADV
fcis-2135	216	5	affected	affect	VERB
fcis-2135	216	6	by	by	ADP
fcis-2135	216	7	surrounding	surround	VERB
fcis-2135	216	8	pedestrians	pedestrian	NOUN
fcis-2135	216	9	and	and	CCONJ
fcis-2135	216	10	their	their	PRON
fcis-2135	216	11	obstacles	obstacle	NOUN
fcis-2135	216	12	(	(	PUNCT
fcis-2135	216	13	buildings	building	NOUN
fcis-2135	216	14	,	,	PUNCT
fcis-2135	216	15	sidewalks	sidewalk	NOUN
fcis-2135	216	16	,	,	PUNCT
fcis-2135	216	17	grasslands	grassland	NOUN
fcis-2135	216	18	,	,	PUNCT
fcis-2135	216	19	etc	etc	X
fcis-2135	216	20	.	.	X
fcis-2135	216	21	)	)	PUNCT
fcis-2135	216	22	,	,	PUNCT
fcis-2135	216	23	which	which	PRON
fcis-2135	216	24	may	may	AUX
fcis-2135	216	25	change	change	VERB
fcis-2135	216	26	or	or	CCONJ
fcis-2135	216	27	limit	limit	VERB
fcis-2135	216	28	human	human	ADJ
fcis-2135	216	29	activities	activity	NOUN
fcis-2135	216	30	.	.	PUNCT
fcis-2135	217	1	therefore	therefore	ADV
fcis-2135	217	2	,	,	PUNCT
fcis-2135	217	3	it	it	PRON
fcis-2135	217	4	is	be	AUX
fcis-2135	217	5	necessary	necessary	ADJ
fcis-2135	217	6	to	to	PART
fcis-2135	217	7	pay	pay	VERB
fcis-2135	217	8	attention	attention	NOUN
fcis-2135	217	9	to	to	ADP
fcis-2135	217	10	the	the	DET
fcis-2135	217	11	factors	factor	NOUN
fcis-2135	217	12	that	that	PRON
fcis-2135	217	13	have	have	VERB
fcis-2135	217	14	great	great	ADJ
fcis-2135	217	15	influence	influence	NOUN
fcis-2135	217	16	on	on	ADP
fcis-2135	217	17	pedestrian	pedestrian	NOUN
fcis-2135	217	18	trajectory	trajectory	NOUN
fcis-2135	217	19	prediction	prediction	NOUN
fcis-2135	217	20	.	.	PUNCT
fcis-2135	218	1	in	in	ADP
fcis-2135	218	2	order	order	NOUN
fcis-2135	218	3	to	to	PART
fcis-2135	218	4	capture	capture	VERB
fcis-2135	218	5	the	the	DET
fcis-2135	218	6	interaction	interaction	NOUN
fcis-2135	218	7	between	between	ADP
fcis-2135	218	8	pedestrians	pedestrian	NOUN
fcis-2135	218	9	and	and	CCONJ
fcis-2135	218	10	neighbors	neighbor	NOUN
fcis-2135	218	11	,	,	PUNCT
fcis-2135	218	12	some	some	DET
fcis-2135	218	13	methods	method	NOUN
fcis-2135	218	14	calculate	calculate	VERB
fcis-2135	218	15	the	the	DET
fcis-2135	218	16	influence	influence	NOUN
fcis-2135	218	17	factor	factor	NOUN
fcis-2135	218	18	of	of	ADP
fcis-2135	218	19	pedestrians	pedestrian	NOUN
fcis-2135	218	20	according	accord	VERB
fcis-2135	218	21	to	to	ADP
fcis-2135	218	22	the	the	DET
fcis-2135	218	23	distance	distance	NOUN
fcis-2135	218	24	between	between	ADP
fcis-2135	218	25	pedestrians	pedestrian	NOUN
fcis-2135	218	26	[	[	X
fcis-2135	218	27	19,28	19,28	NUM
fcis-2135	218	28	]	]	X
fcis-2135	218	29	.	.	PUNCT
fcis-2135	219	1	when	when	SCONJ
fcis-2135	219	2	aggregating	aggregate	VERB
fcis-2135	219	3	the	the	DET
fcis-2135	219	4	interaction	interaction	NOUN
fcis-2135	219	5	behavior	behavior	NOUN
fcis-2135	219	6	of	of	ADP
fcis-2135	219	7	modeling	modeling	NOUN
fcis-2135	219	8	,	,	PUNCT
fcis-2135	219	9	they	they	PRON
fcis-2135	219	10	are	be	AUX
fcis-2135	219	11	encoded	encode	VERB
fcis-2135	219	12	by	by	ADP
fcis-2135	219	13	pooling	pool	VERB
fcis-2135	219	14	,	,	PUNCT
fcis-2135	219	15	symmetric	symmetric	ADJ
fcis-2135	219	16	function	function	NOUN
fcis-2135	219	17	or	or	CCONJ
fcis-2135	219	18	geometric	geometric	ADJ
fcis-2135	219	19	relationship	relationship	NOUN
fcis-2135	219	20	,	,	PUNCT
fcis-2135	219	21	which	which	PRON
fcis-2135	219	22	is	be	AUX
fcis-2135	219	23	neither	neither	CCONJ
fcis-2135	219	24	intuitive	intuitive	ADJ
fcis-2135	219	25	nor	nor	CCONJ
fcis-2135	219	26	direct	direct	ADJ
fcis-2135	219	27	,	,	PUNCT
fcis-2135	219	28	and	and	CCONJ
fcis-2135	219	29	can	can	AUX
fcis-2135	219	30	not	not	PART
fcis-2135	219	31	fully	fully	ADV
fcis-2135	219	32	interpret	interpret	VERB
fcis-2135	219	33	the	the	DET
fcis-2135	219	34	interaction	interaction	NOUN
fcis-2135	219	35	between	between	ADP
fcis-2135	219	36	pedestrians	pedestrian	NOUN
fcis-2135	219	37	.	.	PUNCT
fcis-2135	220	1	graph	graph	NOUN
fcis-2135	220	2	attention	attention	NOUN
fcis-2135	220	3	network	network	NOUN
fcis-2135	220	4	(	(	PUNCT
fcis-2135	220	5	gat	gat	NOUN
fcis-2135	220	6	)	)	PUNCT
fcis-2135	220	7	uses	use	VERB
fcis-2135	220	8	soft	soft	ADJ
fcis-2135	220	9	attention	attention	NOUN
fcis-2135	220	10	or	or	CCONJ
fcis-2135	220	11	shift	shift	NOUN
fcis-2135	220	12	mechanism	mechanism	NOUN
fcis-2135	220	13	to	to	PART
fcis-2135	220	14	distinguish	distinguish	VERB
fcis-2135	220	15	the	the	DET
fcis-2135	220	16	importance	importance	NOUN
fcis-2135	220	17	of	of	ADP
fcis-2135	220	18	neighbors	neighbor	NOUN
fcis-2135	220	19	,	,	PUNCT
fcis-2135	220	20	and	and	CCONJ
fcis-2135	220	21	realizes	realize	VERB
fcis-2135	220	22	effective	effective	ADJ
fcis-2135	220	23	weighted	weight	VERB
fcis-2135	220	24	message	message	NOUN
fcis-2135	220	25	passing	pass	VERB
fcis-2135	220	26	between	between	ADP
fcis-2135	220	27	nodes	node	NOUN
fcis-2135	220	28	and	and	CCONJ
fcis-2135	220	29	better	well	ADJ
fcis-2135	220	30	group	group	NOUN
fcis-2135	220	31	understanding	understanding	NOUN
fcis-2135	220	32	.	.	PUNCT
fcis-2135	221	1	trajectory	trajectory	NOUN
fcis-2135	221	2	prediction	prediction	NOUN
fcis-2135	221	3	based	base	VERB
fcis-2135	221	4	on	on	ADP
fcis-2135	221	5	graph	graph	NOUN
fcis-2135	221	6	attention	attention	NOUN
fcis-2135	221	7	network	network	NOUN
fcis-2135	221	8	[	[	X
fcis-2135	221	9	51,60,62	51,60,62	NUM
fcis-2135	221	10	-	-	SYM
fcis-2135	221	11	65	65	NUM
fcis-2135	221	12	]	]	PUNCT
fcis-2135	221	13	by	by	ADP
fcis-2135	221	14	capturing	capture	VERB
fcis-2135	221	15	the	the	DET
fcis-2135	221	16	importance	importance	NOUN
fcis-2135	221	17	of	of	ADP
fcis-2135	221	18	the	the	DET
fcis-2135	221	19	surrounding	surround	VERB
fcis-2135	221	20	pedestrians	pedestrian	NOUN
fcis-2135	221	21	to	to	ADP
fcis-2135	221	22	the	the	DET
fcis-2135	221	23	target	target	NOUN
fcis-2135	221	24	pedestrians	pedestrian	NOUN
fcis-2135	221	25	,	,	PUNCT
fcis-2135	221	26	it	it	PRON
fcis-2135	221	27	breaks	break	VERB
fcis-2135	221	28	the	the	DET
fcis-2135	221	29	order	order	NOUN
fcis-2135	221	30	dependence	dependence	NOUN
fcis-2135	221	31	of	of	ADP
fcis-2135	221	32	the	the	DET
fcis-2135	221	33	rnn	rnn	NOUN
fcis-2135	221	34	network	network	NOUN
fcis-2135	221	35	and	and	CCONJ
fcis-2135	221	36	provides	provide	VERB
fcis-2135	221	37	a	a	DET
fcis-2135	221	38	more	more	ADV
fcis-2135	221	39	intuitive	intuitive	ADJ
fcis-2135	221	40	method	method	NOUN
fcis-2135	221	41	for	for	ADP
fcis-2135	221	42	reproducing	reproduce	VERB
fcis-2135	221	43	the	the	DET
fcis-2135	221	44	topology	topology	NOUN
fcis-2135	221	45	of	of	ADP
fcis-2135	221	46	pedestrians	pedestrian	NOUN
fcis-2135	221	47	in	in	ADP
fcis-2135	221	48	the	the	DET
fcis-2135	221	49	shared	share	VERB
fcis-2135	221	50	space	space	NOUN
fcis-2135	221	51	.	.	PUNCT
fcis-2135	222	1	however	however	ADV
fcis-2135	222	2	,	,	PUNCT
fcis-2135	222	3	most	most	ADJ
fcis-2135	222	4	of	of	ADP
fcis-2135	222	5	the	the	DET
fcis-2135	222	6	existing	exist	VERB
fcis-2135	222	7	methods	method	NOUN
fcis-2135	222	8	are	be	AUX
fcis-2135	222	9	based	base	VERB
fcis-2135	222	10	on	on	ADP
fcis-2135	222	11	the	the	DET
fcis-2135	222	12	study	study	NOUN
fcis-2135	222	13	of	of	ADP
fcis-2135	222	14	the	the	DET
fcis-2135	222	15	spatial	spatial	ADJ
fcis-2135	222	16	and	and	CCONJ
fcis-2135	222	17	temporal	temporal	ADJ
fcis-2135	222	18	characteristics	characteristic	NOUN
fcis-2135	222	19	of	of	ADP
fcis-2135	222	20	the	the	DET
fcis-2135	222	21	trajectory	trajectory	NOUN
fcis-2135	222	22	.	.	PUNCT
fcis-2135	223	1	the	the	DET
fcis-2135	223	2	spatial	spatial	ADJ
fcis-2135	223	3	information	information	NOUN
fcis-2135	223	4	representation	representation	NOUN
fcis-2135	223	5	is	be	AUX
fcis-2135	223	6	single	single	ADJ
fcis-2135	223	7	,	,	PUNCT
fcis-2135	223	8	ignoring	ignore	VERB
fcis-2135	223	9	the	the	DET
fcis-2135	223	10	deep	deep	ADJ
fcis-2135	223	11	motion	motion	NOUN
fcis-2135	223	12	characteristics	characteristic	NOUN
fcis-2135	223	13	in	in	ADP
fcis-2135	223	14	the	the	DET
fcis-2135	223	15	process	process	NOUN
fcis-2135	223	16	of	of	ADP
fcis-2135	223	17	pedestrian	pedestrian	NOUN
fcis-2135	223	18	movement	movement	NOUN
fcis-2135	223	19	,	,	PUNCT
fcis-2135	223	20	such	such	ADJ
fcis-2135	223	21	as	as	ADP
fcis-2135	223	22	motion	motion	NOUN
fcis-2135	223	23	speed	speed	NOUN
fcis-2135	223	24	,	,	PUNCT
fcis-2135	223	25	motion	motion	NOUN
fcis-2135	223	26	direction	direction	NOUN
fcis-2135	223	27	,	,	PUNCT
fcis-2135	223	28	motion	motion	NOUN
fcis-2135	223	29	state	state	NOUN
fcis-2135	223	30	,	,	PUNCT
fcis-2135	223	31	etc	etc	X
fcis-2135	223	32	.	.	X
fcis-2135	223	33	,	,	PUNCT
fcis-2135	223	34	and	and	CCONJ
fcis-2135	223	35	this	this	DET
fcis-2135	223	36	multi	multi	ADJ
fcis-2135	223	37	-	-	ADJ
fcis-2135	223	38	feature	feature	ADJ
fcis-2135	223	39	information	information	NOUN
fcis-2135	223	40	is	be	AUX
fcis-2135	223	41	more	more	ADV
fcis-2135	223	42	in	in	ADP
fcis-2135	223	43	line	line	NOUN
fcis-2135	223	44	with	with	ADP
fcis-2135	223	45	the	the	DET
fcis-2135	223	46	real	real	ADJ
fcis-2135	223	47	scene	scene	NOUN
fcis-2135	223	48	.	.	PUNCT
fcis-2135	224	1	pedestrian	pedestrian	NOUN
fcis-2135	224	2	motion	motion	NOUN
fcis-2135	224	3	state	state	NOUN
fcis-2135	224	4	has	have	VERB
fcis-2135	224	5	more	more	ADJ
fcis-2135	224	6	application	application	NOUN
fcis-2135	224	7	value	value	NOUN
fcis-2135	224	8	.	.	PUNCT
fcis-2135	225	1	the	the	DET
fcis-2135	225	2	comparison	comparison	NOUN
fcis-2135	225	3	of	of	ADP
fcis-2135	225	4	gcn	gcn	NOUN
fcis-2135	225	5	-	-	PUNCT
fcis-2135	225	6	based	base	VERB
fcis-2135	225	7	pedestrian	pedestrian	NOUN
fcis-2135	225	8	trajectory	trajectory	NOUN
fcis-2135	225	9	prediction	prediction	NOUN
fcis-2135	225	10	methods	method	NOUN
fcis-2135	225	11	is	be	AUX
fcis-2135	225	12	shown	show	VERB
fcis-2135	225	13	in	in	ADP
fcis-2135	225	14	table	table	NOUN
fcis-2135	225	15	3	3	NUM
fcis-2135	225	16	.	.	PUNCT
fcis-2135	225	17	table	table	NOUN
fcis-2135	225	18	3	3	NUM
fcis-2135	225	19	.	.	PUNCT
fcis-2135	225	20	comparison	comparison	NOUN
fcis-2135	225	21	of	of	ADP
fcis-2135	225	22	pedestrian	pedestrian	NOUN
fcis-2135	225	23	trajectory	trajectory	NOUN
fcis-2135	225	24	prediction	prediction	NOUN
fcis-2135	225	25	methods	method	NOUN
fcis-2135	225	26	based	base	VERB
fcis-2135	225	27	on	on	ADP
fcis-2135	225	28	gcn	gcn	NOUN
fcis-2135	225	29	method	method	NOUN
fcis-2135	225	30	advantage	advantage	NOUN
fcis-2135	225	31	shortcoming	shortcoming	NOUN
fcis-2135	225	32	research	research	NOUN
fcis-2135	225	33	direction	direction	NOUN
fcis-2135	225	34	loss	loss	NOUN
fcis-2135	225	35	function	function	NOUN
fcis-2135	225	36	rsgb	rsgb	NOUN
fcis-2135	225	37	[	[	X
fcis-2135	225	38	25	25	NUM
fcis-2135	225	39	]	]	X
fcis-2135	225	40	supervised	supervised	ADJ
fcis-2135	225	41	recursion	recursion	NOUN
fcis-2135	225	42	insufficient	insufficient	ADJ
fcis-2135	225	43	interaction	interaction	NOUN
fcis-2135	225	44	scene	scene	NOUN
fcis-2135	225	45	interaction	interaction	NOUN
fcis-2135	225	46	index	index	NOUN
fcis-2135	225	47	l2	l2	NOUN
fcis-2135	225	48	zhang	zhang	PROPN
fcis-2135	226	1	[	[	X
fcis-2135	226	2	49	49	NUM
fcis-2135	226	3	]	]	PUNCT
fcis-2135	226	4	time	time	NOUN
fcis-2135	226	5	light	light	PROPN
fcis-2135	226	6	code	code	PROPN
fcis-2135	226	7	poor	poor	ADJ
fcis-2135	226	8	stability	stability	NOUN
fcis-2135	226	9	intertextuality	intertextuality	NOUN
fcis-2135	226	10	reconstruction+	reconstruction+	ADP
fcis-2135	226	11	kl	kl	PROPN
fcis-2135	226	12	s	s	PROPN
fcis-2135	226	13	-	-	PUNCT
fcis-2135	226	14	bigat[51	bigat[51	NOUN
fcis-2135	226	15	]	]	PUNCT
fcis-2135	226	16	multimodal	multimodal	NOUN
fcis-2135	226	17	trajectory	trajectory	NOUN
fcis-2135	226	18	insufficient	insufficient	ADJ
fcis-2135	226	19	features	feature	VERB
fcis-2135	226	20	deep	deep	ADJ
fcis-2135	226	21	interaction	interaction	NOUN
fcis-2135	226	22	reconstruction+confrontation+kl+l2+classification	reconstruction+confrontation+kl+l2+classification	NOUN
fcis-2135	226	23	stgat	stgat	NOUN
fcis-2135	226	24	[	[	X
fcis-2135	226	25	60	60	NUM
fcis-2135	226	26	]	]	X
fcis-2135	226	27	serial	serial	ADJ
fcis-2135	226	28	gat	gat	NOUN
fcis-2135	226	29	simplify	simplify	NOUN
fcis-2135	226	30	interaction	interaction	NOUN
fcis-2135	226	31	supervisory	supervisory	ADJ
fcis-2135	226	32	attention	attention	NOUN
fcis-2135	226	33	l2	l2	NOUN
fcis-2135	226	34	loss	loss	NOUN
fcis-2135	226	35	ivanovic	ivanovic	PROPN
fcis-2135	227	1	[	[	X
fcis-2135	227	2	61	61	NUM
fcis-2135	227	3	]	]	SYM
fcis-2135	227	4	multi	multi	ADJ
fcis-2135	227	5	model	model	NOUN
fcis-2135	227	6	and	and	CCONJ
fcis-2135	227	7	multi	multi	ADJ
fcis-2135	227	8	person	person	NOUN
fcis-2135	227	9	computing	compute	VERB
fcis-2135	227	10	overhead	overhead	ADV
fcis-2135	227	11	building	build	VERB
fcis-2135	227	12	dynamic	dynamic	ADJ
fcis-2135	227	13	map	map	NOUN
fcis-2135	227	14	negative	negative	ADJ
fcis-2135	227	15	logarithmic	logarithmic	ADJ
fcis-2135	227	16	likelihood	likelihood	NOUN
fcis-2135	227	17	s	s	NOUN
fcis-2135	227	18	-	-	PUNCT
fcis-2135	227	19	stgcnn	stgcnn	NOUN
fcis-2135	227	20	[	[	X
fcis-2135	227	21	62	62	NUM
fcis-2135	227	22	]	]	PUNCT
fcis-2135	227	23	application	application	NOUN
fcis-2135	227	24	of	of	ADP
fcis-2135	227	25	graph	graph	NOUN
fcis-2135	227	26	time	time	NOUN
fcis-2135	227	27	domain	domain	NOUN
fcis-2135	227	28	independence	independence	NOUN
fcis-2135	227	29	application	application	NOUN
fcis-2135	227	30	expansion	expansion	NOUN
fcis-2135	227	31	negative	negative	ADJ
fcis-2135	227	32	logarithmic	logarithmic	ADJ
fcis-2135	227	33	likelihood	likelihood	NOUN
fcis-2135	227	34	graphtcn[63	graphtcn[63	NOUN
fcis-2135	227	35	]	]	PUNCT
fcis-2135	227	36	gating	gate	VERB
fcis-2135	227	37	adaptation	adaptation	NOUN
fcis-2135	227	38	single	single	ADJ
fcis-2135	227	39	feature	feature	NOUN
fcis-2135	227	40	lack	lack	NOUN
fcis-2135	227	41	of	of	ADP
fcis-2135	227	42	flexibility	flexibility	NOUN
fcis-2135	227	43	ade	ade	NOUN
fcis-2135	227	44	loss	loss	NOUN
fcis-2135	227	45	haddad	haddad	PROPN
fcis-2135	228	1	[	[	X
fcis-2135	228	2	64	64	NUM
fcis-2135	228	3	]	]	PUNCT
fcis-2135	228	4	dynamic	dynamic	ADJ
fcis-2135	228	5	static	static	ADJ
fcis-2135	228	6	interaction	interaction	NOUN
fcis-2135	228	7	local	local	ADJ
fcis-2135	228	8	interaction	interaction	NOUN
fcis-2135	228	9	type	type	NOUN
fcis-2135	228	10	promotion	promotion	NOUN
fcis-2135	228	11	negative	negative	ADJ
fcis-2135	228	12	logarithmic	logarithmic	ADJ
fcis-2135	228	13	likelihood	likelihood	NOUN
fcis-2135	228	14	star	star	NOUN
fcis-2135	228	15	[	[	X
fcis-2135	228	16	65	65	NUM
fcis-2135	228	17	]	]	X
fcis-2135	228	18	novel	novel	ADJ
fcis-2135	228	19	framework	framework	NOUN
fcis-2135	228	20	scene	scene	NOUN
fcis-2135	228	21	missing	miss	VERB
fcis-2135	228	22	application	application	NOUN
fcis-2135	228	23	promotion	promotion	NOUN
fcis-2135	228	24	mean	mean	VERB
fcis-2135	228	25	square	square	ADJ
fcis-2135	228	26	error	error	NOUN
fcis-2135	228	27	4	4	NUM
fcis-2135	228	28	.	.	PUNCT
fcis-2135	229	1	data	datum	NOUN
fcis-2135	229	2	set	set	VERB
fcis-2135	229	3	and	and	CCONJ
fcis-2135	229	4	performance	performance	NOUN
fcis-2135	229	5	comparison	comparison	NOUN
fcis-2135	229	6	4.1	4.1	NUM
fcis-2135	229	7	.	.	PUNCT
fcis-2135	230	1	data	datum	NOUN
fcis-2135	230	2	set	set	VERB
fcis-2135	230	3	introduction	introduction	NOUN
fcis-2135	230	4	in	in	ADP
fcis-2135	230	5	the	the	DET
fcis-2135	230	6	pedestrian	pedestrian	NOUN
fcis-2135	230	7	trajectory	trajectory	NOUN
fcis-2135	230	8	prediction	prediction	NOUN
fcis-2135	230	9	method	method	NOUN
fcis-2135	230	10	based	base	VERB
fcis-2135	230	11	on	on	ADP
fcis-2135	230	12	depth	depth	NOUN
fcis-2135	230	13	learning	learning	NOUN
fcis-2135	230	14	,	,	PUNCT
fcis-2135	230	15	the	the	DET
fcis-2135	230	16	data	data	NOUN
fcis-2135	230	17	sets	set	NOUN
fcis-2135	230	18	involved	involve	VERB
fcis-2135	230	19	mainly	mainly	ADV
fcis-2135	230	20	include	include	VERB
fcis-2135	230	21	eth	eth	PROPN
fcis-2135	230	22	/	/	SYM
fcis-2135	230	23	ucy	ucy	PROPN
fcis-2135	230	24	,	,	PUNCT
fcis-2135	230	25	sdd	sdd	NOUN
fcis-2135	230	26	,	,	PUNCT
fcis-2135	230	27	dut	dut	PROPN
fcis-2135	230	28	,	,	PUNCT
fcis-2135	230	29	actev	actev	NOUN
fcis-2135	230	30	/	/	SYM
fcis-2135	230	31	virat	virat	PROPN
fcis-2135	230	32	,	,	PUNCT
fcis-2135	230	33	town	town	NOUN
fcis-2135	230	34	center	center	NOUN
fcis-2135	230	35	,	,	PUNCT
fcis-2135	230	36	pets09s2	pets09s2	PROPN
fcis-2135	230	37	,	,	PUNCT
fcis-2135	230	38	edinburgh	edinburgh	NOUN
fcis-2135	230	39	,	,	PUNCT
fcis-2135	230	40	interaction	interaction	NOUN
fcis-2135	230	41	,	,	PUNCT
fcis-2135	230	42	dut	dut	PROPN
fcis-2135	230	43	and	and	CCONJ
fcis-2135	230	44	the	the	DET
fcis-2135	230	45	data	data	NOUN
fcis-2135	230	46	sets	set	NOUN
fcis-2135	230	47	of	of	ADP
fcis-2135	230	48	osaki	osaki	NOUN
fcis-2135	230	49	station	station	NOUN
fcis-2135	230	50	,	,	PUNCT
fcis-2135	230	51	grand	grand	ADJ
fcis-2135	230	52	central	central	ADJ
fcis-2135	230	53	and	and	CCONJ
fcis-2135	230	54	cuhk	cuhk	ADJ
fcis-2135	230	55	for	for	ADP
fcis-2135	230	56	crowded	crowded	ADJ
fcis-2135	230	57	scenes	scene	NOUN
fcis-2135	230	58	.	.	PUNCT
fcis-2135	231	1	the	the	DET
fcis-2135	231	2	eth	eth	NOUN
fcis-2135	231	3	and	and	CCONJ
fcis-2135	231	4	ucy	ucy	PROPN
fcis-2135	231	5	combined	combine	VERB
fcis-2135	231	6	data	datum	NOUN
fcis-2135	231	7	set	set	VERB
fcis-2135	231	8	is	be	AUX
fcis-2135	231	9	a	a	DET
fcis-2135	231	10	widely	widely	ADV
fcis-2135	231	11	used	use	VERB
fcis-2135	231	12	public	public	ADJ
fcis-2135	231	13	dataset	dataset	NOUN
fcis-2135	231	14	for	for	ADP
fcis-2135	231	15	evaluating	evaluate	VERB
fcis-2135	231	16	pedestrian	pedestrian	NOUN
fcis-2135	231	17	trajectory	trajectory	NOUN
fcis-2135	231	18	prediction	prediction	NOUN
fcis-2135	231	19	methods	method	NOUN
fcis-2135	231	20	.	.	PUNCT
fcis-2135	232	1	the	the	DET
fcis-2135	232	2	data	datum	NOUN
fcis-2135	232	3	set	set	VERB
fcis-2135	232	4	include	include	VERB
fcis-2135	232	5	the	the	DET
fcis-2135	232	6	global	global	ADJ
fcis-2135	232	7	trajectory	trajectory	NOUN
fcis-2135	232	8	coordinates	coordinate	NOUN
fcis-2135	232	9	of	of	ADP
fcis-2135	232	10	pedestrians	pedestrian	NOUN
fcis-2135	232	11	in	in	ADP
fcis-2135	232	12	various	various	ADJ
fcis-2135	232	13	types	type	NOUN
fcis-2135	232	14	of	of	ADP
fcis-2135	232	15	social	social	ADJ
fcis-2135	232	16	interaction	interaction	NOUN
fcis-2135	232	17	scenarios	scenario	NOUN
fcis-2135	232	18	.	.	PUNCT
fcis-2135	233	1	these	these	DET
fcis-2135	233	2	data	datum	NOUN
fcis-2135	233	3	sets	set	NOUN
fcis-2135	233	4	include	include	VERB
fcis-2135	233	5	the	the	DET
fcis-2135	233	6	trajectory	trajectory	NOUN
fcis-2135	233	7	coordinates	coordinate	NOUN
fcis-2135	233	8	of	of	ADP
fcis-2135	233	9	pedestrian	pedestrian	NOUN
fcis-2135	233	10	interaction	interaction	NOUN
fcis-2135	233	11	,	,	PUNCT
fcis-2135	233	12	nonlinear	nonlinear	ADJ
fcis-2135	233	13	trajectory	trajectory	NOUN
fcis-2135	233	14	,	,	PUNCT
fcis-2135	233	15	collision	collision	NOUN
fcis-2135	233	16	avoidance	avoidance	NOUN
fcis-2135	233	17	,	,	PUNCT
fcis-2135	233	18	standing	standing	NOUN
fcis-2135	233	19	and	and	CCONJ
fcis-2135	233	20	group	group	NOUN
fcis-2135	233	21	pedestrians	pedestrian	NOUN
fcis-2135	233	22	,	,	PUNCT
fcis-2135	233	23	etc	etc	X
fcis-2135	233	24	.	.	X
fcis-2135	233	25	,	,	PUNCT
fcis-2135	233	26	as	as	ADV
fcis-2135	233	27	well	well	ADV
fcis-2135	233	28	as	as	ADP
fcis-2135	233	29	five	five	NUM
fcis-2135	233	30	unique	unique	ADJ
fcis-2135	233	31	outdoor	outdoor	ADJ
fcis-2135	233	32	environment	environment	NOUN
fcis-2135	233	33	information	information	NOUN
fcis-2135	233	34	recorded	record	VERB
fcis-2135	233	35	from	from	ADP
fcis-2135	233	36	the	the	DET
fcis-2135	233	37	fixed	fix	VERB
fcis-2135	233	38	top	top	ADJ
fcis-2135	233	39	view	view	NOUN
fcis-2135	233	40	.	.	PUNCT
fcis-2135	234	1	table	table	NOUN
fcis-2135	234	2	4	4	NUM
fcis-2135	234	3	shows	show	VERB
fcis-2135	234	4	the	the	DET
fcis-2135	234	5	detailed	detailed	ADJ
fcis-2135	234	6	introduction	introduction	NOUN
fcis-2135	234	7	of	of	ADP
fcis-2135	234	8	eth	eth	PROPN
fcis-2135	234	9	/	/	SYM
fcis-2135	234	10	ucy	ucy	PROPN
fcis-2135	234	11	data	datum	NOUN
fcis-2135	234	12	set	set	VERB
fcis-2135	234	13	.	.	PUNCT
fcis-2135	235	1	table	table	NOUN
fcis-2135	235	2	4	4	NUM
fcis-2135	235	3	.	.	PUNCT
fcis-2135	235	4	eth	eth	PROPN
fcis-2135	235	5	/	/	SYM
fcis-2135	235	6	ucy	ucy	PROPN
fcis-2135	235	7	dataset	dataset	VERB
fcis-2135	235	8	scene	scene	NOUN
fcis-2135	235	9	frames	frame	VERB
fcis-2135	235	10	people	people	NOUN
fcis-2135	235	11	groups	group	NOUN
fcis-2135	235	12	obstacles	obstacle	NOUN
fcis-2135	235	13	eth	eth	X
fcis-2135	235	14	1448	1448	NUM
fcis-2135	235	15	360	360	NUM
fcis-2135	235	16	243	243	NUM
fcis-2135	235	17	44	44	NUM
fcis-2135	235	18	hotel	hotel	NOUN
fcis-2135	235	19	1168	1168	NUM
fcis-2135	235	20	390	390	NUM
fcis-2135	235	21	326	326	NUM
fcis-2135	235	22	25	25	NUM
fcis-2135	235	23	univ	univ	ADJ
fcis-2135	235	24	541	541	NUM
fcis-2135	235	25	434	434	NUM
fcis-2135	235	26	297	297	NUM
fcis-2135	235	27	16	16	NUM
fcis-2135	235	28	zara1	zara1	NOUN
fcis-2135	236	1	866	866	NUM
fcis-2135	236	2	148	148	NUM
fcis-2135	236	3	91	91	NUM
fcis-2135	236	4	34	34	NUM
fcis-2135	236	5	zara1	zara1	NOUN
fcis-2135	236	6	1052	1052	NUM
fcis-2135	236	7	204	204	NUM
fcis-2135	236	8	140	140	NUM
fcis-2135	236	9	34	34	NUM
fcis-2135	236	10	the	the	DET
fcis-2135	236	11	sdd	sdd	PROPN
fcis-2135	236	12	data	datum	NOUN
fcis-2135	236	13	set	set	VERB
fcis-2135	236	14	is	be	AUX
fcis-2135	236	15	a	a	DET
fcis-2135	236	16	video	video	NOUN
fcis-2135	236	17	shot	shoot	VERB
fcis-2135	236	18	by	by	ADP
fcis-2135	236	19	robicquet	robicquet	NOUN
fcis-2135	236	20	a	a	PRON
fcis-2135	236	21	et	et	NOUN
fcis-2135	236	22	al	al	PROPN
fcis-2135	236	23	.	.	PUNCT
fcis-2135	237	1	[	[	X
fcis-2135	237	2	66	66	NUM
fcis-2135	237	3	]	]	PUNCT
fcis-2135	237	4	using	use	VERB
fcis-2135	237	5	uavs	uavs	NOUN
fcis-2135	237	6	over	over	ADP
fcis-2135	237	7	the	the	DET
fcis-2135	237	8	stanford	stanford	PROPN
fcis-2135	237	9	university	university	PROPN
fcis-2135	237	10	campus	campus	NOUN
fcis-2135	237	11	from	from	ADP
fcis-2135	237	12	an	an	DET
fcis-2135	237	13	74	74	NUM
fcis-2135	237	14	overhead	overhead	NOUN
fcis-2135	237	15	perspective	perspective	NOUN
fcis-2135	237	16	,	,	PUNCT
fcis-2135	237	17	covering	cover	VERB
fcis-2135	237	18	20	20	NUM
fcis-2135	237	19	different	different	ADJ
fcis-2135	237	20	scenes	scene	NOUN
fcis-2135	237	21	,	,	PUNCT
fcis-2135	237	22	which	which	PRON
fcis-2135	237	23	involve	involve	VERB
fcis-2135	237	24	both	both	DET
fcis-2135	237	25	dynamic	dynamic	ADJ
fcis-2135	237	26	objects	object	NOUN
fcis-2135	237	27	and	and	CCONJ
fcis-2135	237	28	the	the	DET
fcis-2135	237	29	coordinate	coordinate	NOUN
fcis-2135	237	30	positions	position	NOUN
fcis-2135	237	31	of	of	ADP
fcis-2135	237	32	static	static	ADJ
fcis-2135	237	33	obstacles	obstacle	NOUN
fcis-2135	237	34	and	and	CCONJ
fcis-2135	237	35	objects	object	NOUN
fcis-2135	237	36	;	;	PUNCT
fcis-2135	237	37	actev	actev	NOUN
fcis-2135	237	38	/	/	SYM
fcis-2135	237	39	virat	virat	PROPN
fcis-2135	237	40	dataset	dataset	NOUN
fcis-2135	237	41	is	be	AUX
fcis-2135	237	42	a	a	DET
fcis-2135	237	43	public	public	ADJ
fcis-2135	237	44	dataset	dataset	NOUN
fcis-2135	237	45	for	for	ADP
fcis-2135	237	46	behavior	behavior	NOUN
fcis-2135	237	47	detection	detection	NOUN
fcis-2135	237	48	,	,	PUNCT
fcis-2135	237	49	involving	involve	VERB
fcis-2135	237	50	12	12	NUM
fcis-2135	237	51	scenarios	scenario	NOUN
fcis-2135	237	52	.	.	PUNCT
fcis-2135	238	1	the	the	DET
fcis-2135	238	2	total	total	ADJ
fcis-2135	238	3	duration	duration	NOUN
fcis-2135	238	4	of	of	ADP
fcis-2135	238	5	the	the	DET
fcis-2135	238	6	video	video	NOUN
fcis-2135	238	7	is	be	AUX
fcis-2135	238	8	more	more	ADJ
fcis-2135	238	9	than	than	ADP
fcis-2135	238	10	12h	12h	NUM
fcis-2135	238	11	,	,	PUNCT
fcis-2135	238	12	and	and	CCONJ
fcis-2135	238	13	the	the	DET
fcis-2135	238	14	video	video	NOUN
fcis-2135	238	15	contains	contain	VERB
fcis-2135	238	16	rich	rich	ADJ
fcis-2135	238	17	annotations	annotation	NOUN
fcis-2135	238	18	,	,	PUNCT
fcis-2135	238	19	which	which	PRON
fcis-2135	238	20	can	can	AUX
fcis-2135	238	21	last	last	VERB
fcis-2135	238	22	up	up	ADP
fcis-2135	238	23	to	to	ADP
fcis-2135	238	24	4.5h	4.5h	NUM
fcis-2135	238	25	.	.	PUNCT
fcis-2135	239	1	the	the	DET
fcis-2135	239	2	town	town	NOUN
fcis-2135	239	3	center	center	NOUN
fcis-2135	239	4	dataset	dataset	NOUN
fcis-2135	239	5	(	(	PUNCT
fcis-2135	239	6	1	1	NUM
fcis-2135	239	7	video	video	NOUN
fcis-2135	239	8	)	)	PUNCT
fcis-2135	239	9	,	,	PUNCT
fcis-2135	239	10	the	the	DET
fcis-2135	239	11	pets09s2	pets09s2	PROPN
fcis-2135	239	12	dataset	dataset	NOUN
fcis-2135	239	13	(	(	PUNCT
fcis-2135	239	14	3	3	NUM
fcis-2135	239	15	videos	video	NOUN
fcis-2135	239	16	)	)	PUNCT
fcis-2135	239	17	,	,	PUNCT
fcis-2135	239	18	and	and	CCONJ
fcis-2135	239	19	the	the	DET
fcis-2135	239	20	grand	grand	ADJ
fcis-2135	239	21	central	central	ADJ
fcis-2135	239	22	dataset	dataset	NOUN
fcis-2135	239	23	(	(	PUNCT
fcis-2135	239	24	1	1	NUM
fcis-2135	239	25	video	video	NOUN
fcis-2135	239	26	)	)	PUNCT
fcis-2135	239	27	were	be	AUX
fcis-2135	239	28	originally	originally	ADV
fcis-2135	239	29	used	use	VERB
fcis-2135	239	30	for	for	ADP
fcis-2135	239	31	target	target	NOUN
fcis-2135	239	32	tracking	tracking	NOUN
fcis-2135	239	33	and	and	CCONJ
fcis-2135	239	34	crowd	crowd	NOUN
fcis-2135	239	35	behavior	behavior	NOUN
fcis-2135	239	36	analysis	analysis	NOUN
fcis-2135	239	37	.	.	PUNCT
fcis-2135	240	1	these	these	DET
fcis-2135	240	2	three	three	NUM
fcis-2135	240	3	datasets	dataset	NOUN
fcis-2135	240	4	have	have	VERB
fcis-2135	240	5	a	a	DET
fcis-2135	240	6	short	short	ADJ
fcis-2135	240	7	video	video	NOUN
fcis-2135	240	8	time	time	NOUN
fcis-2135	240	9	,	,	PUNCT
fcis-2135	240	10	but	but	CCONJ
fcis-2135	240	11	they	they	PRON
fcis-2135	240	12	contain	contain	VERB
fcis-2135	240	13	a	a	DET
fcis-2135	240	14	lot	lot	NOUN
fcis-2135	240	15	of	of	ADP
fcis-2135	240	16	social	social	ADJ
fcis-2135	240	17	interaction	interaction	NOUN
fcis-2135	240	18	.	.	PUNCT
fcis-2135	241	1	the	the	DET
fcis-2135	241	2	edinburgh	edinburgh	PROPN
fcis-2135	241	3	data	data	PROPN
fcis-2135	241	4	set	set	VERB
fcis-2135	241	5	is	be	AUX
fcis-2135	241	6	the	the	DET
fcis-2135	241	7	pedestrian	pedestrian	NOUN
fcis-2135	241	8	movement	movement	NOUN
fcis-2135	241	9	track	track	NOUN
fcis-2135	241	10	collected	collect	VERB
fcis-2135	241	11	on	on	ADP
fcis-2135	241	12	the	the	DET
fcis-2135	241	13	information	information	NOUN
fcis-2135	241	14	forum	forum	PROPN
fcis-2135	241	15	of	of	ADP
fcis-2135	241	16	edinburgh	edinburgh	PROPN
fcis-2135	241	17	university	university	PROPN
fcis-2135	241	18	.	.	PUNCT
fcis-2135	242	1	the	the	DET
fcis-2135	242	2	collection	collection	NOUN
fcis-2135	242	3	time	time	NOUN
fcis-2135	242	4	lasts	last	VERB
fcis-2135	242	5	for	for	ADP
fcis-2135	242	6	several	several	ADJ
fcis-2135	242	7	months	month	NOUN
fcis-2135	242	8	,	,	PUNCT
fcis-2135	242	9	including	include	VERB
fcis-2135	242	10	92000	92000	NUM
fcis-2135	242	11	tracks	track	NOUN
fcis-2135	242	12	in	in	ADP
fcis-2135	242	13	total	total	NOUN
fcis-2135	242	14	.	.	PUNCT
fcis-2135	243	1	the	the	DET
fcis-2135	243	2	interaction	interaction	NOUN
fcis-2135	243	3	data	datum	NOUN
fcis-2135	243	4	set	set	VERB
fcis-2135	243	5	is	be	AUX
fcis-2135	243	6	jointly	jointly	ADV
fcis-2135	243	7	collected	collect	VERB
fcis-2135	243	8	by	by	ADP
fcis-2135	243	9	uav	uav	PROPN
fcis-2135	243	10	and	and	CCONJ
fcis-2135	243	11	vehicle	vehicle	NOUN
fcis-2135	243	12	mounted	mount	VERB
fcis-2135	243	13	lidar	lidar	NOUN
fcis-2135	243	14	,	,	PUNCT
fcis-2135	243	15	and	and	CCONJ
fcis-2135	243	16	the	the	DET
fcis-2135	243	17	observation	observation	NOUN
fcis-2135	243	18	track	track	NOUN
fcis-2135	243	19	is	be	AUX
fcis-2135	243	20	obtained	obtain	VERB
fcis-2135	243	21	through	through	ADP
fcis-2135	243	22	visual	visual	ADJ
fcis-2135	243	23	inspection	inspection	NOUN
fcis-2135	243	24	technology	technology	NOUN
fcis-2135	243	25	.	.	PUNCT
fcis-2135	244	1	the	the	DET
fcis-2135	244	2	dut	dut	PROPN
fcis-2135	244	3	dataset	dataset	NOUN
fcis-2135	244	4	includes	include	VERB
fcis-2135	244	5	the	the	DET
fcis-2135	244	6	sections	section	NOUN
fcis-2135	244	7	with	with	ADP
fcis-2135	244	8	typical	typical	ADJ
fcis-2135	244	9	mixed	mixed	ADJ
fcis-2135	244	10	traffic	traffic	NOUN
fcis-2135	244	11	characteristics	characteristic	NOUN
fcis-2135	244	12	in	in	ADP
fcis-2135	244	13	the	the	DET
fcis-2135	244	14	main	main	ADJ
fcis-2135	244	15	campus	campus	NOUN
fcis-2135	244	16	of	of	ADP
fcis-2135	244	17	dalian	dalian	PROPN
fcis-2135	244	18	university	university	PROPN
fcis-2135	244	19	of	of	ADP
fcis-2135	244	20	technology	technology	NOUN
fcis-2135	244	21	acquired	acquire	VERB
fcis-2135	244	22	through	through	ADP
fcis-2135	244	23	aerial	aerial	ADJ
fcis-2135	244	24	photography	photography	NOUN
fcis-2135	244	25	,	,	PUNCT
fcis-2135	244	26	including	include	VERB
fcis-2135	244	27	17	17	NUM
fcis-2135	244	28	intersection	intersection	NOUN
fcis-2135	244	29	scene	scene	NOUN
fcis-2135	244	30	clips	clip	NOUN
fcis-2135	244	31	and	and	CCONJ
fcis-2135	244	32	11	11	NUM
fcis-2135	244	33	roundabout	roundabout	ADJ
fcis-2135	244	34	scene	scene	NOUN
fcis-2135	244	35	clips	clip	NOUN
fcis-2135	244	36	,	,	PUNCT
fcis-2135	244	37	including	include	VERB
fcis-2135	244	38	1793	1793	NUM
fcis-2135	244	39	tracks	track	NOUN
fcis-2135	244	40	in	in	ADP
fcis-2135	244	41	total	total	NOUN
fcis-2135	244	42	.	.	PUNCT
fcis-2135	245	1	the	the	DET
fcis-2135	245	2	osaki	osaki	PROPN
fcis-2135	245	3	station	station	NOUN
fcis-2135	245	4	data	datum	NOUN
fcis-2135	245	5	set	set	VERB
fcis-2135	245	6	is	be	AUX
fcis-2135	245	7	the	the	DET
fcis-2135	245	8	trajectory	trajectory	NOUN
fcis-2135	245	9	data	datum	NOUN
fcis-2135	245	10	collected	collect	VERB
fcis-2135	245	11	in	in	ADP
fcis-2135	245	12	osaka	osaka	PROPN
fcis-2135	245	13	station	station	NOUN
fcis-2135	245	14	,	,	PUNCT
fcis-2135	245	15	tokyo	tokyo	PROPN
fcis-2135	245	16	,	,	PUNCT
fcis-2135	245	17	japan	japan	PROPN
fcis-2135	245	18	,	,	PUNCT
fcis-2135	245	19	using	use	VERB
fcis-2135	245	20	two	two	NUM
fcis-2135	245	21	-	-	PUNCT
fcis-2135	245	22	dimensional	dimensional	ADJ
fcis-2135	245	23	laser	laser	NOUN
fcis-2135	245	24	sensors	sensor	NOUN
fcis-2135	245	25	.	.	PUNCT
fcis-2135	246	1	the	the	DET
fcis-2135	246	2	laser	laser	NOUN
fcis-2135	246	3	sensors	sensor	NOUN
fcis-2135	246	4	can	can	AUX
fcis-2135	246	5	also	also	ADV
fcis-2135	246	6	accurately	accurately	ADV
fcis-2135	246	7	obtain	obtain	VERB
fcis-2135	246	8	the	the	DET
fcis-2135	246	9	position	position	NOUN
fcis-2135	246	10	of	of	ADP
fcis-2135	246	11	pedestrians	pedestrian	NOUN
fcis-2135	246	12	in	in	ADP
fcis-2135	246	13	groups	group	NOUN
fcis-2135	246	14	when	when	SCONJ
fcis-2135	246	15	pedestrians	pedestrian	NOUN
fcis-2135	246	16	block	block	VERB
fcis-2135	246	17	each	each	DET
fcis-2135	246	18	other	other	ADJ
fcis-2135	246	19	.	.	PUNCT
fcis-2135	247	1	cuhk	cuhk	PROPN
fcis-2135	247	2	dataset	dataset	PROPN
fcis-2135	247	3	is	be	AUX
fcis-2135	247	4	a	a	DET
fcis-2135	247	5	crowd	crowd	NOUN
fcis-2135	247	6	dataset	dataset	VERB
fcis-2135	247	7	with	with	ADP
fcis-2135	247	8	different	different	ADJ
fcis-2135	247	9	density	density	NOUN
fcis-2135	247	10	and	and	CCONJ
fcis-2135	247	11	different	different	ADJ
fcis-2135	247	12	angles	angle	NOUN
fcis-2135	247	13	shot	shoot	VERB
fcis-2135	247	14	in	in	ADP
fcis-2135	247	15	many	many	ADJ
fcis-2135	247	16	scenes	scene	NOUN
fcis-2135	247	17	,	,	PUNCT
fcis-2135	247	18	including	include	VERB
fcis-2135	247	19	real	real	ADJ
fcis-2135	247	20	track	track	NOUN
fcis-2135	247	21	,	,	PUNCT
fcis-2135	247	22	group	group	NOUN
fcis-2135	247	23	status	status	NOUN
fcis-2135	247	24	,	,	PUNCT
fcis-2135	247	25	crowd	crowd	VERB
fcis-2135	247	26	video	video	NOUN
fcis-2135	247	27	classification	classification	NOUN
fcis-2135	247	28	,	,	PUNCT
fcis-2135	247	29	etc	etc	X
fcis-2135	247	30	.	.	X
fcis-2135	247	31	4.2	4.2	NUM
fcis-2135	247	32	.	.	PUNCT
fcis-2135	247	33	evaluation	evaluation	NOUN
fcis-2135	247	34	index	index	NOUN
fcis-2135	247	35	as	as	ADP
fcis-2135	247	36	a	a	DET
fcis-2135	247	37	subproblem	subproblem	NOUN
fcis-2135	247	38	of	of	ADP
fcis-2135	247	39	the	the	DET
fcis-2135	247	40	prediction	prediction	NOUN
fcis-2135	247	41	problem	problem	NOUN
fcis-2135	247	42	,	,	PUNCT
fcis-2135	247	43	pedestrian	pedestrian	NOUN
fcis-2135	247	44	trajectory	trajectory	NOUN
fcis-2135	247	45	prediction	prediction	NOUN
fcis-2135	247	46	is	be	AUX
fcis-2135	247	47	essentially	essentially	ADV
fcis-2135	247	48	a	a	DET
fcis-2135	247	49	sequence	sequence	NOUN
fcis-2135	247	50	generation	generation	NOUN
fcis-2135	247	51	problem	problem	NOUN
fcis-2135	247	52	.	.	PUNCT
fcis-2135	248	1	the	the	DET
fcis-2135	248	2	input	input	NOUN
fcis-2135	248	3	sequence	sequence	NOUN
fcis-2135	248	4	of	of	ADP
fcis-2135	248	5	the	the	DET
fcis-2135	248	6	problem	problem	NOUN
fcis-2135	248	7	corresponds	correspond	VERB
fcis-2135	248	8	to	to	ADP
fcis-2135	248	9	all	all	DET
fcis-2135	248	10	the	the	DET
fcis-2135	248	11	observed	observed	ADJ
fcis-2135	248	12	pedestrian	pedestrian	NOUN
fcis-2135	248	13	positions	position	NOUN
fcis-2135	248	14	,	,	PUNCT
fcis-2135	248	15	and	and	CCONJ
fcis-2135	248	16	the	the	DET
fcis-2135	248	17	output	output	NOUN
fcis-2135	248	18	sequence	sequence	NOUN
fcis-2135	248	19	represents	represent	VERB
fcis-2135	248	20	the	the	DET
fcis-2135	248	21	position	position	NOUN
fcis-2135	248	22	of	of	ADP
fcis-2135	248	23	the	the	DET
fcis-2135	248	24	pedestrian	pedestrian	NOUN
fcis-2135	248	25	in	in	ADP
fcis-2135	248	26	the	the	DET
fcis-2135	248	27	future	future	NOUN
fcis-2135	248	28	.	.	PUNCT
fcis-2135	249	1	assuming	assume	VERB
fcis-2135	249	2	that	that	SCONJ
fcis-2135	249	3	at	at	ADP
fcis-2135	249	4	any	any	DET
fcis-2135	249	5	time	time	NOUN
fcis-2135	249	6	t	t	PROPN
fcis-2135	249	7	,	,	PUNCT
fcis-2135	249	8	the	the	DET
fcis-2135	249	9	number	number	NOUN
fcis-2135	249	10	of	of	ADP
fcis-2135	249	11	pedestrians	pedestrian	NOUN
fcis-2135	249	12	is	be	AUX
fcis-2135	249	13	n	n	PRON
fcis-2135	249	14	,	,	PUNCT
fcis-2135	249	15	the	the	DET
fcis-2135	249	16	actual	actual	ADJ
fcis-2135	249	17	position	position	NOUN
fcis-2135	249	18	of	of	ADP
fcis-2135	249	19	pedestrian	pedestrian	NOUN
fcis-2135	249	20	i	i	PROPN
fcis-2135	249	21	in	in	ADP
fcis-2135	249	22	the	the	DET
fcis-2135	249	23	scene	scene	NOUN
fcis-2135	249	24	is	be	AUX
fcis-2135	249	25	expressed	express	VERB
fcis-2135	249	26	as	as	ADP
fcis-2135	249	27	(	(	PUNCT
fcis-2135	249	28	xit	xit	PROPN
fcis-2135	249	29	,	,	PUNCT
fcis-2135	249	30	yit	yit	PROPN
fcis-2135	249	31	)	)	PUNCT
fcis-2135	249	32	,	,	PUNCT
fcis-2135	249	33	the	the	DET
fcis-2135	249	34	position	position	NOUN
fcis-2135	249	35	sequence	sequence	NOUN
fcis-2135	249	36	of	of	ADP
fcis-2135	249	37	all	all	DET
fcis-2135	249	38	pedestrians	pedestrian	NOUN
fcis-2135	249	39	from	from	ADP
fcis-2135	249	40	time	time	NOUN
fcis-2135	249	41	t=1	t=1	ADV
fcis-2135	249	42	to	to	ADP
fcis-2135	249	43	t	t	PROPN
fcis-2135	249	44	=	=	PRON
fcis-2135	249	45	tobs	tob	NOUN
fcis-2135	249	46	(	(	PUNCT
fcis-2135	249	47	obs	obs	PROPN
fcis-2135	249	48	represents	represent	VERB
fcis-2135	249	49	the	the	DET
fcis-2135	249	50	length	length	NOUN
fcis-2135	249	51	of	of	ADP
fcis-2135	249	52	observation	observation	NOUN
fcis-2135	249	53	sequence	sequence	NOUN
fcis-2135	249	54	)	)	PUNCT
fcis-2135	249	55	,	,	PUNCT
fcis-2135	249	56	then	then	ADV
fcis-2135	249	57	the	the	DET
fcis-2135	249	58	observation	observation	NOUN
fcis-2135	249	59	time	time	NOUN
fcis-2135	249	60	t	t	PROPN
fcis-2135	249	61	=	=	NOUN
fcis-2135	249	62	tobs+1	tobs+1	PROPN
fcis-2135	249	63	to	to	ADP
fcis-2135	249	64	t	t	PROPN
fcis-2135	249	65	=	=	SYM
fcis-2135	249	66	tobs+pred	tobs+pred	PROPN
fcis-2135	249	67	(	(	PUNCT
fcis-2135	249	68	pred	pre	VERB
fcis-2135	249	69	represents	represent	VERB
fcis-2135	249	70	the	the	DET
fcis-2135	249	71	length	length	NOUN
fcis-2135	249	72	of	of	ADP
fcis-2135	249	73	prediction	prediction	NOUN
fcis-2135	249	74	sequence	sequence	NOUN
fcis-2135	249	75	)	)	PUNCT
fcis-2135	249	76	,	,	PUNCT
fcis-2135	249	77	and	and	CCONJ
fcis-2135	249	78	the	the	DET
fcis-2135	249	79	prediction	prediction	NOUN
fcis-2135	249	80	position	position	NOUN
fcis-2135	249	81	of	of	ADP
fcis-2135	249	82	all	all	DET
fcis-2135	249	83	pedestrians	pedestrian	NOUN
fcis-2135	249	84	(	(	PUNCT
fcis-2135	249	85	xipt	xipt	PROPN
fcis-2135	249	86	,	,	PUNCT
fcis-2135	249	87	yipt	yipt	PROPN
fcis-2135	249	88	)	)	PUNCT
fcis-2135	249	89	.	.	PUNCT
fcis-2135	250	1	when	when	SCONJ
fcis-2135	250	2	evaluating	evaluate	VERB
fcis-2135	250	3	the	the	DET
fcis-2135	250	4	performance	performance	NOUN
fcis-2135	250	5	of	of	ADP
fcis-2135	250	6	trajectory	trajectory	NOUN
fcis-2135	250	7	prediction	prediction	NOUN
fcis-2135	250	8	methods	method	NOUN
fcis-2135	250	9	,	,	PUNCT
fcis-2135	250	10	the	the	DET
fcis-2135	250	11	average	average	ADJ
fcis-2135	250	12	displacement	displacement	NOUN
fcis-2135	250	13	error	error	NOUN
fcis-2135	250	14	(	(	PUNCT
fcis-2135	250	15	ade	ade	PROPN
fcis-2135	250	16	)	)	PUNCT
fcis-2135	250	17	and	and	CCONJ
fcis-2135	250	18	the	the	DET
fcis-2135	250	19	final	final	ADJ
fcis-2135	250	20	displacement	displacement	NOUN
fcis-2135	250	21	error	error	NOUN
fcis-2135	250	22	(	(	PUNCT
fcis-2135	250	23	fde	fde	NOUN
fcis-2135	250	24	)	)	PUNCT
fcis-2135	250	25	are	be	AUX
fcis-2135	250	26	usually	usually	ADV
fcis-2135	250	27	used	use	VERB
fcis-2135	250	28	to	to	PART
fcis-2135	250	29	predict	predict	VERB
fcis-2135	250	30	and	and	CCONJ
fcis-2135	250	31	evaluate	evaluate	VERB
fcis-2135	250	32	the	the	DET
fcis-2135	250	33	trajectory	trajectory	NOUN
fcis-2135	250	34	of	of	ADP
fcis-2135	250	35	agents	agent	NOUN
fcis-2135	250	36	in	in	ADP
fcis-2135	250	37	each	each	DET
fcis-2135	250	38	scene	scene	NOUN
fcis-2135	250	39	.	.	PUNCT
fcis-2135	251	1	(	(	PUNCT
fcis-2135	251	2	1	1	X
fcis-2135	251	3	)	)	PUNCT
fcis-2135	251	4	ade	ade	NOUN
fcis-2135	251	5	ade	ade	PROPN
fcis-2135	251	6	refers	refer	VERB
fcis-2135	251	7	to	to	ADP
fcis-2135	251	8	the	the	DET
fcis-2135	251	9	average	average	ADJ
fcis-2135	251	10	european	european	ADJ
fcis-2135	251	11	distance	distance	NOUN
fcis-2135	251	12	difference	difference	NOUN
fcis-2135	251	13	between	between	ADP
fcis-2135	251	14	the	the	DET
fcis-2135	251	15	real	real	ADJ
fcis-2135	251	16	track	track	NOUN
fcis-2135	251	17	and	and	CCONJ
fcis-2135	251	18	the	the	DET
fcis-2135	251	19	predicted	predict	VERB
fcis-2135	251	20	track	track	NOUN
fcis-2135	251	21	position	position	NOUN
fcis-2135	251	22	sequence	sequence	NOUN
fcis-2135	251	23	of	of	ADP
fcis-2135	251	24	each	each	DET
fcis-2135	251	25	pedestrian	pedestrian	NOUN
fcis-2135	251	26	in	in	ADP
fcis-2135	251	27	each	each	DET
fcis-2135	251	28	time	time	NOUN
fcis-2135	251	29	step	step	NOUN
fcis-2135	251	30	,	,	PUNCT
fcis-2135	251	31	which	which	PRON
fcis-2135	251	32	is	be	AUX
fcis-2135	251	33	used	use	VERB
fcis-2135	251	34	to	to	PART
fcis-2135	251	35	evaluate	evaluate	VERB
fcis-2135	251	36	the	the	DET
fcis-2135	251	37	overall	overall	ADJ
fcis-2135	251	38	performance	performance	NOUN
fcis-2135	251	39	of	of	ADP
fcis-2135	251	40	the	the	DET
fcis-2135	251	41	prediction	prediction	NOUN
fcis-2135	251	42	process	process	NOUN
fcis-2135	251	43	,	,	PUNCT
fcis-2135	251	44	as	as	SCONJ
fcis-2135	251	45	shown	show	VERB
fcis-2135	251	46	in	in	ADP
fcis-2135	251	47	formula	formula	NOUN
fcis-2135	251	48	(	(	PUNCT
fcis-2135	251	49	1	1	NUM
fcis-2135	251	50	)	)	PUNCT
fcis-2135	251	51	.	.	PUNCT
fcis-2135	252	1	𝐴𝐷𝐸	𝐴𝐷𝐸	PROPN
fcis-2135	252	2	=	=	SYM
fcis-2135	252	3	1	1	NUM
fcis-2135	252	4	𝑛	𝑛	DET
fcis-2135	252	5	∑	∑	SYM
fcis-2135	252	6	1	1	NUM
fcis-2135	252	7	𝑝𝑟𝑒𝑑	𝑝𝑟𝑒𝑑	NOUN
fcis-2135	252	8	𝑛	𝑛	PRON
fcis-2135	252	9	𝑖=1	𝑖=1	PUNCT
fcis-2135	252	10	∑	∑	PROPN
fcis-2135	252	11	√(𝑥𝑖	√(𝑥𝑖	PROPN
fcis-2135	252	12	𝑇	𝑇	PROPN
fcis-2135	252	13	−	−	PROPN
fcis-2135	252	14	𝑥𝑖𝑝	𝑥𝑖𝑝	PROPN
fcis-2135	252	15	𝑇	𝑇	PROPN
fcis-2135	252	16	)	)	PUNCT
fcis-2135	252	17	2	2	NUM
fcis-2135	253	1	+	+	CCONJ
fcis-2135	253	2	(	(	PUNCT
fcis-2135	253	3	𝑦𝑖	𝑦𝑖	PROPN
fcis-2135	253	4	𝑇	𝑇	PROPN
fcis-2135	253	5	−	−	PROPN
fcis-2135	253	6	𝑦𝑖𝑝	𝑦𝑖𝑝	PROPN
fcis-2135	253	7	𝑇	𝑇	PROPN
fcis-2135	253	8	)	)	PUNCT
fcis-2135	253	9	2	2	NUM
fcis-2135	253	10	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	PROPN
fcis-2135	253	11	𝑇=𝑇𝑜𝑏𝑠+1	𝑇=𝑇𝑜𝑏𝑠+1	NOUN
fcis-2135	253	12	(	(	PUNCT
fcis-2135	253	13	2	2	NUM
fcis-2135	253	14	)	)	PUNCT
fcis-2135	253	15	fde	fde	PROPN
fcis-2135	253	16	fde	fde	PROPN
fcis-2135	253	17	refers	refer	VERB
fcis-2135	253	18	to	to	ADP
fcis-2135	253	19	the	the	DET
fcis-2135	253	20	average	average	ADJ
fcis-2135	253	21	euclidean	euclidean	ADJ
fcis-2135	253	22	distance	distance	NOUN
fcis-2135	253	23	difference	difference	NOUN
fcis-2135	253	24	between	between	ADP
fcis-2135	253	25	the	the	DET
fcis-2135	253	26	real	real	ADJ
fcis-2135	253	27	track	track	NOUN
fcis-2135	253	28	and	and	CCONJ
fcis-2135	253	29	the	the	DET
fcis-2135	253	30	predicted	predict	VERB
fcis-2135	253	31	track	track	NOUN
fcis-2135	253	32	of	of	ADP
fcis-2135	253	33	each	each	DET
fcis-2135	253	34	pedestrian	pedestrian	NOUN
fcis-2135	253	35	at	at	ADP
fcis-2135	253	36	the	the	DET
fcis-2135	253	37	destination	destination	NOUN
fcis-2135	253	38	,	,	PUNCT
fcis-2135	253	39	as	as	SCONJ
fcis-2135	253	40	shown	show	VERB
fcis-2135	253	41	in	in	ADP
fcis-2135	253	42	formula	formula	NOUN
fcis-2135	253	43	(	(	PUNCT
fcis-2135	253	44	2	2	NUM
fcis-2135	253	45	)	)	PUNCT
fcis-2135	253	46	.	.	PUNCT
fcis-2135	254	1	𝐹𝐷𝐸	𝐹𝐷𝐸	PROPN
fcis-2135	254	2	=	=	SYM
fcis-2135	254	3	1	1	NUM
fcis-2135	254	4	𝑛	𝑛	NOUN
fcis-2135	254	5	∑√(𝑥	∑√(𝑥	X
fcis-2135	254	6	𝑖	𝑖	SYM
fcis-2135	254	7	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	PROPN
fcis-2135	254	8	−	−	ADP
fcis-2135	254	9	𝑥	𝑥	NOUN
fcis-2135	254	10	𝑖𝑝	𝑖𝑝	INTJ
fcis-2135	254	11	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑)2	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑)2	X
fcis-2135	254	12	+	+	X
fcis-2135	254	13	(	(	PUNCT
fcis-2135	254	14	𝑦	𝑦	NOUN
fcis-2135	254	15	𝑖	𝑖	PRON
fcis-2135	254	16	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑	PROPN
fcis-2135	254	17	−	−	PUNCT
fcis-2135	254	18	𝑦	𝑦	SYM
fcis-2135	254	19	𝑖𝑝	𝑖𝑝	INTJ
fcis-2135	254	20	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑)2	𝑇𝑜𝑏𝑠+𝑝𝑟𝑒𝑑)2	PROPN
fcis-2135	254	21	𝑛	𝑛	PRON
fcis-2135	254	22	𝑖=1	𝑖=1	PROPN
fcis-2135	254	23	4.3	4.3	NUM
fcis-2135	254	24	.	.	PUNCT
fcis-2135	255	1	performance	performance	NOUN
fcis-2135	255	2	comparison	comparison	NOUN
fcis-2135	255	3	at	at	ADP
fcis-2135	255	4	present	present	ADJ
fcis-2135	255	5	,	,	PUNCT
fcis-2135	255	6	eth	eth	PROPN
fcis-2135	255	7	and	and	CCONJ
fcis-2135	255	8	ucy	ucy	PROPN
fcis-2135	255	9	datasets	dataset	NOUN
fcis-2135	255	10	are	be	AUX
fcis-2135	255	11	widely	widely	ADV
fcis-2135	255	12	used	use	VERB
fcis-2135	255	13	in	in	ADP
fcis-2135	255	14	the	the	DET
fcis-2135	255	15	field	field	NOUN
fcis-2135	255	16	of	of	ADP
fcis-2135	255	17	pedestrian	pedestrian	NOUN
fcis-2135	255	18	trajectory	trajectory	NOUN
fcis-2135	255	19	prediction	prediction	NOUN
fcis-2135	255	20	.	.	PUNCT
fcis-2135	256	1	although	although	SCONJ
fcis-2135	256	2	many	many	ADJ
fcis-2135	256	3	data	datum	NOUN
fcis-2135	256	4	sets	set	NOUN
fcis-2135	256	5	for	for	ADP
fcis-2135	256	6	trajectory	trajectory	NOUN
fcis-2135	256	7	prediction	prediction	NOUN
fcis-2135	256	8	also	also	ADV
fcis-2135	256	9	appeared	appear	VERB
fcis-2135	256	10	in	in	ADP
fcis-2135	256	11	the	the	DET
fcis-2135	256	12	later	later	ADJ
fcis-2135	256	13	stage	stage	NOUN
fcis-2135	256	14	,	,	PUNCT
fcis-2135	256	15	due	due	ADP
fcis-2135	256	16	to	to	ADP
fcis-2135	256	17	the	the	DET
fcis-2135	256	18	relatively	relatively	ADV
fcis-2135	256	19	late	late	ADJ
fcis-2135	256	20	appearance	appearance	NOUN
fcis-2135	256	21	of	of	ADP
fcis-2135	256	22	these	these	DET
fcis-2135	256	23	data	datum	NOUN
fcis-2135	256	24	sets	set	NOUN
fcis-2135	256	25	,	,	PUNCT
fcis-2135	256	26	the	the	DET
fcis-2135	256	27	validation	validation	NOUN
fcis-2135	256	28	of	of	ADP
fcis-2135	256	29	some	some	DET
fcis-2135	256	30	early	early	ADV
fcis-2135	256	31	published	publish	VERB
fcis-2135	256	32	trajectory	trajectory	NOUN
fcis-2135	256	33	prediction	prediction	NOUN
fcis-2135	256	34	methods	method	NOUN
fcis-2135	256	35	on	on	ADP
fcis-2135	256	36	these	these	DET
fcis-2135	256	37	data	datum	NOUN
fcis-2135	256	38	sets	set	NOUN
fcis-2135	256	39	lacks	lack	VERB
fcis-2135	256	40	sufficient	sufficient	ADJ
fcis-2135	256	41	experimental	experimental	ADJ
fcis-2135	256	42	data	datum	NOUN
fcis-2135	256	43	,	,	PUNCT
fcis-2135	256	44	so	so	SCONJ
fcis-2135	256	45	it	it	PRON
fcis-2135	256	46	is	be	AUX
fcis-2135	256	47	difficult	difficult	ADJ
fcis-2135	256	48	to	to	PART
fcis-2135	256	49	accurately	accurately	ADV
fcis-2135	256	50	test	test	VERB
fcis-2135	256	51	the	the	DET
fcis-2135	256	52	effectiveness	effectiveness	NOUN
fcis-2135	256	53	of	of	ADP
fcis-2135	256	54	these	these	DET
fcis-2135	256	55	data	datum	NOUN
fcis-2135	256	56	sets	set	NOUN
fcis-2135	256	57	.	.	PUNCT
fcis-2135	257	1	therefore	therefore	ADV
fcis-2135	257	2	,	,	PUNCT
fcis-2135	257	3	this	this	DET
fcis-2135	257	4	paper	paper	NOUN
fcis-2135	257	5	only	only	ADV
fcis-2135	257	6	compares	compare	VERB
fcis-2135	257	7	the	the	DET
fcis-2135	257	8	performance	performance	NOUN
fcis-2135	257	9	of	of	ADP
fcis-2135	257	10	models	model	NOUN
fcis-2135	257	11	based	base	VERB
fcis-2135	257	12	on	on	ADP
fcis-2135	257	13	eth	eth	PROPN
fcis-2135	257	14	and	and	CCONJ
fcis-2135	257	15	ucy	ucy	PROPN
fcis-2135	257	16	data	datum	NOUN
fcis-2135	257	17	sets	set	NOUN
fcis-2135	257	18	.	.	PUNCT
fcis-2135	258	1	table	table	NOUN
fcis-2135	258	2	5	5	NUM
fcis-2135	258	3	shows	show	VERB
fcis-2135	258	4	the	the	DET
fcis-2135	258	5	performance	performance	NOUN
fcis-2135	258	6	of	of	ADP
fcis-2135	258	7	some	some	DET
fcis-2135	258	8	methods	method	NOUN
fcis-2135	258	9	mentioned	mention	VERB
fcis-2135	258	10	in	in	ADP
fcis-2135	258	11	this	this	DET
fcis-2135	258	12	article	article	NOUN
fcis-2135	258	13	on	on	ADP
fcis-2135	258	14	eth	eth	PROPN
fcis-2135	258	15	and	and	CCONJ
fcis-2135	258	16	ucy	ucy	PROPN
fcis-2135	258	17	datasets	dataset	NOUN
fcis-2135	258	18	.	.	PUNCT
fcis-2135	259	1	it	it	PRON
fcis-2135	259	2	can	can	AUX
fcis-2135	259	3	be	be	AUX
fcis-2135	259	4	seen	see	VERB
fcis-2135	259	5	from	from	ADP
fcis-2135	259	6	table	table	NOUN
fcis-2135	259	7	5	5	NUM
fcis-2135	259	8	that	that	SCONJ
fcis-2135	259	9	the	the	DET
fcis-2135	259	10	trajectory	trajectory	NOUN
fcis-2135	259	11	prediction	prediction	NOUN
fcis-2135	259	12	method	method	NOUN
fcis-2135	259	13	based	base	VERB
fcis-2135	259	14	on	on	ADP
fcis-2135	259	15	deep	deep	ADJ
fcis-2135	259	16	learning	learning	NOUN
fcis-2135	259	17	has	have	VERB
fcis-2135	259	18	better	well	ADJ
fcis-2135	259	19	effect	effect	NOUN
fcis-2135	259	20	,	,	PUNCT
fcis-2135	259	21	and	and	CCONJ
fcis-2135	259	22	the	the	DET
fcis-2135	259	23	recognition	recognition	NOUN
fcis-2135	259	24	accuracy	accuracy	NOUN
fcis-2135	259	25	is	be	AUX
fcis-2135	259	26	much	much	ADV
fcis-2135	259	27	higher	high	ADJ
fcis-2135	259	28	than	than	ADP
fcis-2135	259	29	that	that	PRON
fcis-2135	259	30	based	base	VERB
fcis-2135	259	31	on	on	ADP
fcis-2135	259	32	traditional	traditional	ADJ
fcis-2135	259	33	shallow	shallow	ADJ
fcis-2135	259	34	learning	learning	NOUN
fcis-2135	259	35	method	method	NOUN
fcis-2135	259	36	,	,	PUNCT
fcis-2135	259	37	which	which	PRON
fcis-2135	259	38	shows	show	VERB
fcis-2135	259	39	extremely	extremely	ADV
fcis-2135	259	40	excellent	excellent	ADJ
fcis-2135	259	41	performance	performance	NOUN
fcis-2135	259	42	in	in	ADP
fcis-2135	259	43	eth	eth	PROPN
fcis-2135	259	44	and	and	CCONJ
fcis-2135	259	45	ucy	ucy	PROPN
fcis-2135	259	46	data	datum	NOUN
fcis-2135	259	47	sets	set	NOUN
fcis-2135	259	48	.	.	PUNCT
fcis-2135	260	1	with	with	ADP
fcis-2135	260	2	the	the	DET
fcis-2135	260	3	development	development	NOUN
fcis-2135	260	4	of	of	ADP
fcis-2135	260	5	generative	generative	ADJ
fcis-2135	260	6	network	network	NOUN
fcis-2135	260	7	and	and	CCONJ
fcis-2135	260	8	graph	graph	NOUN
fcis-2135	260	9	based	base	VERB
fcis-2135	260	10	neural	neural	ADJ
fcis-2135	260	11	network	network	NOUN
fcis-2135	260	12	technology	technology	NOUN
fcis-2135	260	13	and	and	CCONJ
fcis-2135	260	14	the	the	DET
fcis-2135	260	15	combination	combination	NOUN
fcis-2135	260	16	of	of	ADP
fcis-2135	260	17	these	these	DET
fcis-2135	260	18	two	two	NUM
fcis-2135	260	19	networks	network	NOUN
fcis-2135	260	20	and	and	CCONJ
fcis-2135	260	21	various	various	ADJ
fcis-2135	260	22	semantic	semantic	ADJ
fcis-2135	260	23	scene	scene	NOUN
fcis-2135	260	24	information	information	NOUN
fcis-2135	260	25	,	,	PUNCT
fcis-2135	260	26	the	the	DET
fcis-2135	260	27	test	test	NOUN
fcis-2135	260	28	performance	performance	NOUN
fcis-2135	260	29	of	of	ADP
fcis-2135	260	30	many	many	ADJ
fcis-2135	260	31	trajectory	trajectory	NOUN
fcis-2135	260	32	prediction	prediction	NOUN
fcis-2135	260	33	methods	method	NOUN
fcis-2135	260	34	on	on	ADP
fcis-2135	260	35	the	the	DET
fcis-2135	260	36	public	public	ADJ
fcis-2135	260	37	data	datum	NOUN
fcis-2135	260	38	set	set	VERB
fcis-2135	260	39	is	be	AUX
fcis-2135	260	40	increasingly	increasingly	ADV
fcis-2135	260	41	excellent	excellent	ADJ
fcis-2135	260	42	.	.	PUNCT
fcis-2135	261	1	among	among	ADP
fcis-2135	261	2	them	they	PRON
fcis-2135	261	3	,	,	PUNCT
fcis-2135	261	4	the	the	DET
fcis-2135	261	5	learning	learning	NOUN
fcis-2135	261	6	method	method	NOUN
fcis-2135	261	7	based	base	VERB
fcis-2135	261	8	on	on	ADP
fcis-2135	261	9	generative	generative	ADJ
fcis-2135	261	10	countermeasure	countermeasure	NOUN
fcis-2135	261	11	network	network	NOUN
fcis-2135	261	12	represented	represent	VERB
fcis-2135	261	13	by	by	ADP
fcis-2135	261	14	social	social	ADJ
fcis-2135	261	15	ways	way	NOUN
fcis-2135	261	16	has	have	VERB
fcis-2135	261	17	more	more	ADV
fcis-2135	261	18	significant	significant	ADJ
fcis-2135	261	19	performance	performance	NOUN
fcis-2135	261	20	and	and	CCONJ
fcis-2135	261	21	relatively	relatively	ADV
fcis-2135	261	22	high	high	ADJ
fcis-2135	261	23	recognition	recognition	NOUN
fcis-2135	261	24	rate	rate	NOUN
fcis-2135	261	25	.	.	PUNCT
fcis-2135	262	1	the	the	DET
fcis-2135	262	2	ade	ade	PROPN
fcis-2135	262	3	value	value	NOUN
fcis-2135	262	4	and	and	CCONJ
fcis-2135	262	5	fde	fde	NOUN
fcis-2135	262	6	value	value	NOUN
fcis-2135	262	7	of	of	ADP
fcis-2135	262	8	social	social	ADJ
fcis-2135	262	9	ways	way	NOUN
fcis-2135	262	10	method	method	NOUN
fcis-2135	262	11	reach	reach	VERB
fcis-2135	262	12	0.45	0.45	NUM
fcis-2135	262	13	and	and	CCONJ
fcis-2135	262	14	0.81	0.81	NUM
fcis-2135	262	15	respectively	respectively	ADV
fcis-2135	262	16	,	,	PUNCT
fcis-2135	262	17	the	the	DET
fcis-2135	262	18	performance	performance	NOUN
fcis-2135	262	19	of	of	ADP
fcis-2135	262	20	the	the	DET
fcis-2135	262	21	proposed	propose	VERB
fcis-2135	262	22	method	method	NOUN
fcis-2135	262	23	is	be	AUX
fcis-2135	262	24	greatly	greatly	ADV
fcis-2135	262	25	improved	improve	VERB
fcis-2135	262	26	.	.	PUNCT
fcis-2135	263	1	it	it	PRON
fcis-2135	263	2	can	can	AUX
fcis-2135	263	3	also	also	ADV
fcis-2135	263	4	be	be	AUX
fcis-2135	263	5	found	find	VERB
fcis-2135	263	6	that	that	SCONJ
fcis-2135	263	7	the	the	DET
fcis-2135	263	8	trajectory	trajectory	NOUN
fcis-2135	263	9	prediction	prediction	NOUN
fcis-2135	263	10	methods	method	NOUN
fcis-2135	263	11	based	base	VERB
fcis-2135	263	12	on	on	ADP
fcis-2135	263	13	graph	graph	NOUN
fcis-2135	263	14	networks	network	NOUN
fcis-2135	263	15	(	(	PUNCT
fcis-2135	263	16	gat	gat	NOUN
fcis-2135	263	17	,	,	PUNCT
fcis-2135	263	18	stgat	stgat	NOUN
fcis-2135	263	19	,	,	PUNCT
fcis-2135	263	20	social	social	ADJ
fcis-2135	263	21	bigat	bigat	NOUN
fcis-2135	263	22	,	,	PUNCT
fcis-2135	263	23	tpnet-20	tpnet-20	ADJ
fcis-2135	263	24	,	,	PUNCT
fcis-2135	263	25	social	social	ADJ
fcis-2135	263	26	stgcnn	stgcnn	PROPN
fcis-2135	263	27	)	)	PUNCT
fcis-2135	263	28	are	be	AUX
fcis-2135	263	29	developing	develop	VERB
fcis-2135	263	30	rapidly	rapidly	ADV
fcis-2135	263	31	.	.	PUNCT
fcis-2135	264	1	when	when	SCONJ
fcis-2135	264	2	s	s	NOUN
fcis-2135	264	3	-	-	PUNCT
fcis-2135	264	4	rnn	rnn	PROPN
fcis-2135	264	5	was	be	AUX
fcis-2135	264	6	proposed	propose	VERB
fcis-2135	264	7	,	,	PUNCT
fcis-2135	264	8	the	the	DET
fcis-2135	264	9	performance	performance	NOUN
fcis-2135	264	10	of	of	ADP
fcis-2135	264	11	srnn	srnn	NOUN
fcis-2135	264	12	was	be	AUX
fcis-2135	264	13	only	only	ADV
fcis-2135	264	14	50	50	NUM
fcis-2135	264	15	%	%	NOUN
fcis-2135	264	16	of	of	ADP
fcis-2135	264	17	that	that	PRON
fcis-2135	264	18	based	base	VERB
fcis-2135	264	19	on	on	ADP
fcis-2135	264	20	lstm	lstm	PROPN
fcis-2135	264	21	.	.	PUNCT
fcis-2135	265	1	however	however	ADV
fcis-2135	265	2	,	,	PUNCT
fcis-2135	265	3	with	with	ADP
fcis-2135	265	4	the	the	DET
fcis-2135	265	5	improvement	improvement	NOUN
fcis-2135	265	6	of	of	ADP
fcis-2135	265	7	graph	graph	NOUN
fcis-2135	265	8	models	model	NOUN
fcis-2135	265	9	and	and	CCONJ
fcis-2135	265	10	the	the	DET
fcis-2135	265	11	application	application	NOUN
fcis-2135	265	12	of	of	ADP
fcis-2135	265	13	gcn	gcn	NOUN
fcis-2135	265	14	and	and	CCONJ
fcis-2135	265	15	gat	gat	NOUN
fcis-2135	265	16	models	model	NOUN
fcis-2135	265	17	,	,	PUNCT
fcis-2135	265	18	the	the	DET
fcis-2135	265	19	prediction	prediction	NOUN
fcis-2135	265	20	accuracy	accuracy	NOUN
fcis-2135	265	21	of	of	ADP
fcis-2135	265	22	trajectory	trajectory	NOUN
fcis-2135	265	23	prediction	prediction	NOUN
fcis-2135	265	24	methods	method	NOUN
fcis-2135	265	25	based	base	VERB
fcis-2135	265	26	on	on	ADP
fcis-2135	265	27	graph	graph	NOUN
fcis-2135	265	28	networks	network	NOUN
fcis-2135	265	29	was	be	AUX
fcis-2135	265	30	also	also	ADV
fcis-2135	265	31	improved	improve	VERB
fcis-2135	265	32	,	,	PUNCT
fcis-2135	265	33	its	its	PRON
fcis-2135	265	34	prediction	prediction	NOUN
fcis-2135	265	35	effect	effect	NOUN
fcis-2135	265	36	has	have	AUX
fcis-2135	265	37	exceeded	exceed	VERB
fcis-2135	265	38	the	the	DET
fcis-2135	265	39	trajectory	trajectory	NOUN
fcis-2135	265	40	prediction	prediction	NOUN
fcis-2135	265	41	method	method	NOUN
fcis-2135	265	42	based	base	VERB
fcis-2135	265	43	on	on	ADP
fcis-2135	265	44	the	the	DET
fcis-2135	265	45	generative	generative	ADJ
fcis-2135	265	46	network	network	NOUN
fcis-2135	265	47	,	,	PUNCT
fcis-2135	265	48	and	and	CCONJ
fcis-2135	265	49	the	the	DET
fcis-2135	265	50	prediction	prediction	NOUN
fcis-2135	265	51	accuracy	accuracy	NOUN
fcis-2135	265	52	is	be	AUX
fcis-2135	265	53	more	more	ADJ
fcis-2135	265	54	than	than	ADP
fcis-2135	265	55	50	50	NUM
fcis-2135	265	56	%	%	NOUN
fcis-2135	265	57	higher	high	ADJ
fcis-2135	265	58	than	than	ADP
fcis-2135	265	59	s	s	NOUN
fcis-2135	265	60	-	-	PUNCT
fcis-2135	265	61	lstm	lstm	NOUN
fcis-2135	265	62	.	.	PUNCT
fcis-2135	266	1	in	in	ADP
fcis-2135	266	2	a	a	DET
fcis-2135	266	3	word	word	NOUN
fcis-2135	266	4	,	,	PUNCT
fcis-2135	266	5	by	by	ADP
fcis-2135	266	6	reasonably	reasonably	ADV
fcis-2135	266	7	designing	design	VERB
fcis-2135	266	8	the	the	DET
fcis-2135	266	9	network	network	NOUN
fcis-2135	266	10	structure	structure	NOUN
fcis-2135	266	11	and	and	CCONJ
fcis-2135	266	12	loss	loss	NOUN
fcis-2135	266	13	function	function	NOUN
fcis-2135	266	14	,	,	PUNCT
fcis-2135	266	15	the	the	DET
fcis-2135	266	16	trajectory	trajectory	NOUN
fcis-2135	266	17	prediction	prediction	NOUN
fcis-2135	266	18	method	method	NOUN
fcis-2135	266	19	based	base	VERB
fcis-2135	266	20	on	on	ADP
fcis-2135	266	21	deep	deep	ADJ
fcis-2135	266	22	learning	learning	NOUN
fcis-2135	266	23	can	can	AUX
fcis-2135	266	24	relatively	relatively	ADV
fcis-2135	266	25	accurately	accurately	ADV
fcis-2135	266	26	predict	predict	VERB
fcis-2135	266	27	the	the	DET
fcis-2135	266	28	next	next	ADJ
fcis-2135	266	29	trajectories	trajectory	NOUN
fcis-2135	266	30	of	of	ADP
fcis-2135	266	31	travelers	traveler	NOUN
fcis-2135	266	32	,	,	PUNCT
fcis-2135	266	33	and	and	CCONJ
fcis-2135	266	34	can	can	AUX
fcis-2135	266	35	better	well	ADV
fcis-2135	266	36	establish	establish	VERB
fcis-2135	266	37	the	the	DET
fcis-2135	266	38	basic	basic	ADJ
fcis-2135	266	39	framework	framework	NOUN
fcis-2135	266	40	of	of	ADP
fcis-2135	266	41	trajectory	trajectory	NOUN
fcis-2135	266	42	prediction	prediction	NOUN
fcis-2135	266	43	task	task	NOUN
fcis-2135	266	44	.	.	PUNCT
fcis-2135	267	1	problems	problem	NOUN
fcis-2135	267	2	and	and	CCONJ
fcis-2135	267	3	challenges	challenge	NOUN
fcis-2135	267	4	in	in	ADP
fcis-2135	267	5	pedestrian	pedestrian	NOUN
fcis-2135	267	6	trajectory	trajectory	NOUN
fcis-2135	267	7	prediction	prediction	NOUN
fcis-2135	267	8	in	in	ADP
fcis-2135	267	9	recent	recent	ADJ
fcis-2135	267	10	years	year	NOUN
fcis-2135	267	11	,	,	PUNCT
fcis-2135	267	12	although	although	SCONJ
fcis-2135	267	13	significant	significant	ADJ
fcis-2135	267	14	achievements	achievement	NOUN
fcis-2135	267	15	have	have	AUX
fcis-2135	267	16	been	be	AUX
fcis-2135	267	17	made	make	VERB
fcis-2135	267	18	in	in	ADP
fcis-2135	267	19	pedestrian	pedestrian	NOUN
fcis-2135	267	20	trajectory	trajectory	NOUN
fcis-2135	267	21	prediction	prediction	NOUN
fcis-2135	267	22	methods	method	NOUN
fcis-2135	267	23	,	,	PUNCT
fcis-2135	267	24	there	there	PRON
fcis-2135	267	25	are	be	VERB
fcis-2135	267	26	still	still	ADV
fcis-2135	267	27	some	some	DET
fcis-2135	267	28	problems	problem	NOUN
fcis-2135	267	29	.	.	PUNCT
fcis-2135	268	1	the	the	DET
fcis-2135	268	2	prediction	prediction	NOUN
fcis-2135	268	3	algorithm	algorithm	NOUN
fcis-2135	268	4	is	be	AUX
fcis-2135	268	5	not	not	PART
fcis-2135	268	6	adaptable	adaptable	ADJ
fcis-2135	268	7	to	to	ADP
fcis-2135	268	8	the	the	DET
fcis-2135	268	9	environment	environment	NOUN
fcis-2135	268	10	.	.	PUNCT
fcis-2135	269	1	existing	exist	VERB
fcis-2135	269	2	social	social	ADJ
fcis-2135	269	3	perception	perception	NOUN
fcis-2135	269	4	methods	method	NOUN
fcis-2135	269	5	assume	assume	VERB
fcis-2135	269	6	that	that	SCONJ
fcis-2135	269	7	all	all	DET
fcis-2135	269	8	observed	observed	ADJ
fcis-2135	269	9	pedestrian	pedestrian	NOUN
fcis-2135	269	10	behaviors	behavior	NOUN
fcis-2135	269	11	are	be	AUX
fcis-2135	269	12	similar	similar	ADJ
fcis-2135	269	13	,	,	PUNCT
fcis-2135	269	14	and	and	CCONJ
fcis-2135	269	15	their	their	PRON
fcis-2135	269	16	movements	movement	NOUN
fcis-2135	269	17	can	can	AUX
fcis-2135	269	18	be	be	AUX
fcis-2135	269	19	predicted	predict	VERB
fcis-2135	269	20	with	with	ADP
fcis-2135	269	21	the	the	DET
fcis-2135	269	22	same	same	ADJ
fcis-2135	269	23	model	model	NOUN
fcis-2135	269	24	and	and	CCONJ
fcis-2135	269	25	characteristics	characteristic	NOUN
fcis-2135	269	26	,	,	PUNCT
fcis-2135	269	27	and	and	CCONJ
fcis-2135	269	28	the	the	DET
fcis-2135	269	29	capture	capture	NOUN
fcis-2135	269	30	and	and	CCONJ
fcis-2135	269	31	reasoning	reasoning	NOUN
fcis-2135	269	32	of	of	ADP
fcis-2135	269	33	high	high	ADJ
fcis-2135	269	34	-	-	PUNCT
fcis-2135	269	35	level	level	NOUN
fcis-2135	269	36	social	social	ADJ
fcis-2135	269	37	attributes	attribute	NOUN
fcis-2135	269	38	are	be	AUX
fcis-2135	269	39	not	not	PART
fcis-2135	269	40	strong	strong	ADJ
fcis-2135	269	41	.	.	PUNCT
fcis-2135	270	1	most	most	ADJ
fcis-2135	270	2	models	model	NOUN
fcis-2135	270	3	are	be	AUX
fcis-2135	270	4	designed	design	VERB
fcis-2135	270	5	for	for	ADP
fcis-2135	270	6	specific	specific	ADJ
fcis-2135	270	7	scenes	scene	NOUN
fcis-2135	270	8	,	,	PUNCT
fcis-2135	270	9	tasks	task	NOUN
fcis-2135	270	10	,	,	PUNCT
fcis-2135	270	11	or	or	CCONJ
fcis-2135	270	12	motions	motion	NOUN
fcis-2135	270	13	.	.	PUNCT
fcis-2135	271	1	these	these	DET
fcis-2135	271	2	methods	method	NOUN
fcis-2135	271	3	perform	perform	VERB
fcis-2135	271	4	well	well	ADV
fcis-2135	271	5	when	when	SCONJ
fcis-2135	271	6	the	the	DET
fcis-2135	271	7	spatial	spatial	ADJ
fcis-2135	271	8	structure	structure	NOUN
fcis-2135	271	9	is	be	AUX
fcis-2135	271	10	specific	specific	ADJ
fcis-2135	271	11	and	and	CCONJ
fcis-2135	271	12	the	the	DET
fcis-2135	271	13	motion	motion	NOUN
fcis-2135	271	14	mode	mode	NOUN
fcis-2135	271	15	is	be	AUX
fcis-2135	271	16	fixed	fix	VERB
fcis-2135	271	17	,	,	PUNCT
fcis-2135	271	18	for	for	ADP
fcis-2135	271	19	example	example	NOUN
fcis-2135	271	20	,	,	PUNCT
fcis-2135	271	21	when	when	SCONJ
fcis-2135	271	22	the	the	DET
fcis-2135	271	23	motion	motion	NOUN
fcis-2135	271	24	mode	mode	NOUN
fcis-2135	271	25	is	be	AUX
fcis-2135	271	26	significant	significant	ADJ
fcis-2135	271	27	in	in	ADP
fcis-2135	271	28	the	the	DET
fcis-2135	271	29	environment	environment	NOUN
fcis-2135	271	30	and	and	CCONJ
fcis-2135	271	31	the	the	DET
fcis-2135	271	32	spatial	spatial	ADJ
fcis-2135	271	33	structure	structure	NOUN
fcis-2135	271	34	and	and	CCONJ
fcis-2135	271	35	pedestrian	pedestrian	NOUN
fcis-2135	271	36	target	target	NOUN
fcis-2135	271	37	are	be	AUX
fcis-2135	271	38	known	know	VERB
fcis-2135	271	39	,	,	PUNCT
fcis-2135	271	40	but	but	CCONJ
fcis-2135	271	41	the	the	DET
fcis-2135	271	42	performance	performance	NOUN
fcis-2135	271	43	is	be	AUX
fcis-2135	271	44	poor	poor	ADJ
fcis-2135	271	45	in	in	ADP
fcis-2135	271	46	undefined	undefined	ADJ
fcis-2135	271	47	and	and	CCONJ
fcis-2135	271	48	changing	change	VERB
fcis-2135	271	49	situations	situation	NOUN
fcis-2135	271	50	.	.	PUNCT
fcis-2135	272	1	the	the	DET
fcis-2135	272	2	interaction	interaction	NOUN
fcis-2135	272	3	lacks	lack	VERB
fcis-2135	272	4	interpretability	interpretability	NOUN
fcis-2135	272	5	.	.	PUNCT
fcis-2135	273	1	when	when	SCONJ
fcis-2135	273	2	training	train	VERB
fcis-2135	273	3	the	the	DET
fcis-2135	273	4	network	network	NOUN
fcis-2135	273	5	model	model	NOUN
fcis-2135	273	6	,	,	PUNCT
fcis-2135	273	7	the	the	DET
fcis-2135	273	8	data	datum	NOUN
fcis-2135	273	9	used	use	VERB
fcis-2135	273	10	are	be	AUX
fcis-2135	273	11	objectively	objectively	ADV
fcis-2135	273	12	measurable	measurable	ADJ
fcis-2135	273	13	data	datum	NOUN
fcis-2135	273	14	,	,	PUNCT
fcis-2135	273	15	which	which	PRON
fcis-2135	273	16	can	can	AUX
fcis-2135	273	17	not	not	PART
fcis-2135	273	18	accurately	accurately	ADV
fcis-2135	273	19	grasp	grasp	VERB
fcis-2135	273	20	the	the	DET
fcis-2135	273	21	pedestrian	pedestrian	NOUN
fcis-2135	273	22	movement	movement	NOUN
fcis-2135	273	23	intention	intention	NOUN
fcis-2135	273	24	,	,	PUNCT
fcis-2135	273	25	and	and	CCONJ
fcis-2135	273	26	lack	lack	NOUN
fcis-2135	273	27	of	of	ADP
fcis-2135	273	28	data	datum	NOUN
fcis-2135	273	29	that	that	PRON
fcis-2135	273	30	rely	rely	VERB
fcis-2135	273	31	on	on	ADP
fcis-2135	273	32	human	human	ADJ
fcis-2135	273	33	subjective	subjective	ADJ
fcis-2135	273	34	judgment	judgment	NOUN
fcis-2135	273	35	to	to	PART
fcis-2135	273	36	train	train	VERB
fcis-2135	273	37	the	the	DET
fcis-2135	273	38	algorithm	algorithm	NOUN
fcis-2135	273	39	.	.	PUNCT
fcis-2135	274	1	some	some	DET
fcis-2135	274	2	models	model	NOUN
fcis-2135	274	3	have	have	AUX
fcis-2135	274	4	made	make	VERB
fcis-2135	274	5	75	75	NUM
fcis-2135	274	6	some	some	DET
fcis-2135	274	7	attempts	attempt	NOUN
fcis-2135	274	8	to	to	PART
fcis-2135	274	9	use	use	VERB
fcis-2135	274	10	head	head	NOUN
fcis-2135	274	11	posture	posture	NOUN
fcis-2135	274	12	[	[	X
fcis-2135	274	13	42	42	NUM
fcis-2135	274	14	]	]	PUNCT
fcis-2135	274	15	in	in	ADP
fcis-2135	274	16	combination	combination	NOUN
fcis-2135	274	17	with	with	ADP
fcis-2135	274	18	pedestrian	pedestrian	NOUN
fcis-2135	274	19	behavior	behavior	NOUN
fcis-2135	274	20	prediction	prediction	NOUN
fcis-2135	274	21	[	[	X
fcis-2135	274	22	24	24	NUM
fcis-2135	274	23	]	]	PUNCT
fcis-2135	274	24	,	,	PUNCT
fcis-2135	274	25	but	but	CCONJ
fcis-2135	274	26	the	the	DET
fcis-2135	274	27	way	way	NOUN
fcis-2135	274	28	to	to	PART
fcis-2135	274	29	obtain	obtain	VERB
fcis-2135	274	30	data	datum	NOUN
fcis-2135	274	31	is	be	AUX
fcis-2135	274	32	single	single	ADJ
fcis-2135	274	33	,	,	PUNCT
fcis-2135	274	34	and	and	CCONJ
fcis-2135	274	35	there	there	PRON
fcis-2135	274	36	is	be	VERB
fcis-2135	274	37	little	little	ADJ
fcis-2135	274	38	research	research	NOUN
fcis-2135	274	39	on	on	ADP
fcis-2135	274	40	the	the	DET
fcis-2135	274	41	subjective	subjective	ADJ
fcis-2135	274	42	intentions	intention	NOUN
fcis-2135	274	43	of	of	ADP
fcis-2135	274	44	pedestrians	pedestrian	NOUN
fcis-2135	274	45	.	.	PUNCT
fcis-2135	275	1	therefore	therefore	ADV
fcis-2135	275	2	,	,	PUNCT
fcis-2135	275	3	the	the	DET
fcis-2135	275	4	current	current	ADJ
fcis-2135	275	5	model	model	NOUN
fcis-2135	275	6	is	be	AUX
fcis-2135	275	7	still	still	ADV
fcis-2135	275	8	dependent	dependent	ADJ
fcis-2135	275	9	on	on	ADP
fcis-2135	275	10	data	datum	NOUN
fcis-2135	275	11	-	-	PUNCT
fcis-2135	275	12	driven	drive	VERB
fcis-2135	275	13	because	because	SCONJ
fcis-2135	275	14	of	of	ADP
fcis-2135	275	15	its	its	PRON
fcis-2135	275	16	lack	lack	NOUN
fcis-2135	275	17	of	of	ADP
fcis-2135	275	18	interpretability	interpretability	NOUN
fcis-2135	275	19	for	for	ADP
fcis-2135	275	20	calculated	calculate	VERB
fcis-2135	275	21	interactions	interaction	NOUN
fcis-2135	275	22	.	.	PUNCT
fcis-2135	276	1	the	the	DET
fcis-2135	276	2	dynamic	dynamic	ADJ
fcis-2135	276	3	graph	graph	NOUN
fcis-2135	276	4	lacks	lack	VERB
fcis-2135	276	5	time	time	NOUN
fcis-2135	276	6	sequence	sequence	NOUN
fcis-2135	276	7	correlation	correlation	NOUN
fcis-2135	276	8	.	.	PUNCT
fcis-2135	277	1	in	in	ADP
fcis-2135	277	2	the	the	DET
fcis-2135	277	3	network	network	NOUN
fcis-2135	277	4	architecture	architecture	NOUN
fcis-2135	277	5	based	base	VERB
fcis-2135	277	6	on	on	ADP
fcis-2135	277	7	graph	graph	NOUN
fcis-2135	277	8	structure	structure	NOUN
fcis-2135	277	9	,	,	PUNCT
fcis-2135	277	10	in	in	ADP
fcis-2135	277	11	the	the	DET
fcis-2135	277	12	process	process	NOUN
fcis-2135	277	13	of	of	ADP
fcis-2135	277	14	building	build	VERB
fcis-2135	277	15	dynamic	dynamic	ADJ
fcis-2135	277	16	graph	graph	NOUN
fcis-2135	277	17	in	in	ADP
fcis-2135	277	18	time	time	NOUN
fcis-2135	277	19	sequence	sequence	NOUN
fcis-2135	277	20	,	,	PUNCT
fcis-2135	277	21	there	there	PRON
fcis-2135	277	22	is	be	VERB
fcis-2135	277	23	a	a	DET
fcis-2135	277	24	lack	lack	NOUN
fcis-2135	277	25	of	of	ADP
fcis-2135	277	26	tracking	tracking	NOUN
fcis-2135	277	27	and	and	CCONJ
fcis-2135	277	28	updating	updating	NOUN
fcis-2135	277	29	of	of	ADP
fcis-2135	277	30	relevant	relevant	ADJ
fcis-2135	277	31	information	information	NOUN
fcis-2135	277	32	of	of	ADP
fcis-2135	277	33	targets	target	NOUN
fcis-2135	277	34	at	at	ADP
fcis-2135	277	35	different	different	ADJ
fcis-2135	277	36	times	time	NOUN
fcis-2135	277	37	.	.	PUNCT
fcis-2135	278	1	that	that	PRON
fcis-2135	278	2	is	is	ADV
fcis-2135	278	3	,	,	PUNCT
fcis-2135	278	4	the	the	DET
fcis-2135	278	5	model	model	NOUN
fcis-2135	278	6	can	can	AUX
fcis-2135	278	7	clearly	clearly	ADV
fcis-2135	278	8	obtain	obtain	VERB
fcis-2135	278	9	the	the	DET
fcis-2135	278	10	position	position	NOUN
fcis-2135	278	11	of	of	ADP
fcis-2135	278	12	the	the	DET
fcis-2135	278	13	target	target	NOUN
fcis-2135	278	14	(	(	PUNCT
fcis-2135	278	15	such	such	ADJ
fcis-2135	278	16	as	as	ADP
fcis-2135	278	17	obstacles	obstacle	NOUN
fcis-2135	278	18	)	)	PUNCT
fcis-2135	278	19	at	at	ADP
fcis-2135	278	20	each	each	DET
fcis-2135	278	21	time	time	NOUN
fcis-2135	278	22	point	point	NOUN
fcis-2135	278	23	,	,	PUNCT
fcis-2135	278	24	but	but	CCONJ
fcis-2135	278	25	the	the	DET
fcis-2135	278	26	current	current	ADJ
fcis-2135	278	27	algorithm	algorithm	NOUN
fcis-2135	278	28	does	do	AUX
fcis-2135	278	29	not	not	PART
fcis-2135	278	30	associate	associate	VERB
fcis-2135	278	31	the	the	DET
fcis-2135	278	32	target	target	NOUN
fcis-2135	278	33	in	in	ADP
fcis-2135	278	34	time	time	NOUN
fcis-2135	278	35	sequence	sequence	NOUN
fcis-2135	278	36	,	,	PUNCT
fcis-2135	278	37	and	and	CCONJ
fcis-2135	278	38	the	the	DET
fcis-2135	278	39	network	network	NOUN
fcis-2135	278	40	can	can	AUX
fcis-2135	278	41	not	not	PART
fcis-2135	278	42	understand	understand	VERB
fcis-2135	278	43	the	the	DET
fcis-2135	278	44	corresponding	correspond	VERB
fcis-2135	278	45	relationship	relationship	NOUN
fcis-2135	278	46	between	between	ADP
fcis-2135	278	47	the	the	DET
fcis-2135	278	48	two	two	NUM
fcis-2135	278	49	-	-	PUNCT
fcis-2135	278	50	time	time	NOUN
fcis-2135	278	51	targets	target	NOUN
fcis-2135	278	52	,	,	PUNCT
fcis-2135	278	53	which	which	PRON
fcis-2135	278	54	reduces	reduce	VERB
fcis-2135	278	55	the	the	DET
fcis-2135	278	56	interaction	interaction	NOUN
fcis-2135	278	57	performance	performance	NOUN
fcis-2135	278	58	and	and	CCONJ
fcis-2135	278	59	leads	lead	VERB
fcis-2135	278	60	to	to	ADP
fcis-2135	278	61	the	the	DET
fcis-2135	278	62	instability	instability	NOUN
fcis-2135	278	63	of	of	ADP
fcis-2135	278	64	the	the	DET
fcis-2135	278	65	graph	graph	NOUN
fcis-2135	278	66	network	network	NOUN
fcis-2135	278	67	structure	structure	NOUN
fcis-2135	278	68	.	.	PUNCT
fcis-2135	279	1	the	the	DET
fcis-2135	279	2	understanding	understanding	NOUN
fcis-2135	279	3	of	of	ADP
fcis-2135	279	4	semantic	semantic	ADJ
fcis-2135	279	5	scenarios	scenario	NOUN
fcis-2135	279	6	is	be	AUX
fcis-2135	279	7	not	not	PART
fcis-2135	279	8	deep	deep	ADV
fcis-2135	279	9	enough	enough	ADV
fcis-2135	279	10	.	.	PUNCT
fcis-2135	280	1	the	the	DET
fcis-2135	280	2	semantic	semantic	ADJ
fcis-2135	280	3	understanding	understanding	NOUN
fcis-2135	280	4	of	of	ADP
fcis-2135	280	5	scenes	scene	NOUN
fcis-2135	280	6	is	be	AUX
fcis-2135	280	7	to	to	PART
fcis-2135	280	8	enable	enable	VERB
fcis-2135	280	9	computers	computer	NOUN
fcis-2135	280	10	,	,	PUNCT
fcis-2135	280	11	like	like	ADP
fcis-2135	280	12	human	human	ADJ
fcis-2135	280	13	brains	brain	NOUN
fcis-2135	280	14	,	,	PUNCT
fcis-2135	280	15	to	to	PART
fcis-2135	280	16	correctly	correctly	ADV
fcis-2135	280	17	understand	understand	VERB
fcis-2135	280	18	natural	natural	ADJ
fcis-2135	280	19	scenes	scene	NOUN
fcis-2135	280	20	and	and	CCONJ
fcis-2135	280	21	content	content	NOUN
fcis-2135	280	22	.	.	PUNCT
fcis-2135	281	1	many	many	ADJ
fcis-2135	281	2	existing	exist	VERB
fcis-2135	281	3	models	model	NOUN
fcis-2135	281	4	or	or	CCONJ
fcis-2135	281	5	methods	method	NOUN
fcis-2135	281	6	are	be	AUX
fcis-2135	281	7	limited	limit	VERB
fcis-2135	281	8	to	to	ADP
fcis-2135	281	9	a	a	DET
fcis-2135	281	10	small	small	ADJ
fcis-2135	281	11	range	range	NOUN
fcis-2135	281	12	of	of	ADP
fcis-2135	281	13	context	context	NOUN
fcis-2135	281	14	information	information	NOUN
fcis-2135	281	15	modeling	modeling	NOUN
fcis-2135	281	16	,	,	PUNCT
fcis-2135	281	17	and	and	CCONJ
fcis-2135	281	18	can	can	AUX
fcis-2135	281	19	only	only	ADV
fcis-2135	281	20	learn	learn	VERB
fcis-2135	281	21	local	local	ADJ
fcis-2135	281	22	features	feature	NOUN
fcis-2135	281	23	,	,	PUNCT
fcis-2135	281	24	resulting	result	VERB
fcis-2135	281	25	in	in	ADP
fcis-2135	281	26	the	the	DET
fcis-2135	281	27	semantic	semantic	ADJ
fcis-2135	281	28	understanding	understanding	NOUN
fcis-2135	281	29	of	of	ADP
fcis-2135	281	30	the	the	DET
fcis-2135	281	31	scene	scene	NOUN
fcis-2135	281	32	is	be	AUX
fcis-2135	281	33	hindered	hinder	VERB
fcis-2135	281	34	.	.	PUNCT
fcis-2135	282	1	5	5	X
fcis-2135	282	2	.	.	X
fcis-2135	282	3	future	future	ADJ
fcis-2135	282	4	outlook	outlook	NOUN
fcis-2135	282	5	of	of	ADP
fcis-2135	282	6	pedestrian	pedestrian	NOUN
fcis-2135	282	7	trajectory	trajectory	NOUN
fcis-2135	282	8	prediction	prediction	NOUN
fcis-2135	282	9	learn	learn	VERB
fcis-2135	282	10	and	and	CCONJ
fcis-2135	282	11	summarize	summarize	VERB
fcis-2135	282	12	various	various	ADJ
fcis-2135	282	13	algorithms	algorithm	NOUN
fcis-2135	282	14	to	to	PART
fcis-2135	282	15	improve	improve	VERB
fcis-2135	282	16	the	the	DET
fcis-2135	282	17	adaptability	adaptability	NOUN
fcis-2135	282	18	of	of	ADP
fcis-2135	282	19	the	the	DET
fcis-2135	282	20	model	model	NOUN
fcis-2135	282	21	.	.	PUNCT
fcis-2135	283	1	pay	pay	VERB
fcis-2135	283	2	attention	attention	NOUN
fcis-2135	283	3	to	to	PART
fcis-2135	283	4	transfer	transfer	VERB
fcis-2135	283	5	learning	learning	NOUN
fcis-2135	283	6	and	and	CCONJ
fcis-2135	283	7	method	method	NOUN
fcis-2135	283	8	promotion	promotion	NOUN
fcis-2135	283	9	,	,	PUNCT
fcis-2135	283	10	and	and	CCONJ
fcis-2135	283	11	combine	combine	VERB
fcis-2135	283	12	the	the	DET
fcis-2135	283	13	different	different	ADJ
fcis-2135	283	14	advantages	advantage	NOUN
fcis-2135	283	15	of	of	ADP
fcis-2135	283	16	multiple	multiple	ADJ
fcis-2135	283	17	prediction	prediction	NOUN
fcis-2135	283	18	frameworks	framework	NOUN
fcis-2135	283	19	to	to	PART
fcis-2135	283	20	achieve	achieve	VERB
fcis-2135	283	21	more	more	ADV
fcis-2135	283	22	reliable	reliable	ADJ
fcis-2135	283	23	prediction	prediction	NOUN
fcis-2135	283	24	.	.	PUNCT
fcis-2135	284	1	in	in	ADP
fcis-2135	284	2	the	the	DET
fcis-2135	284	3	new	new	ADJ
fcis-2135	284	4	environment	environment	NOUN
fcis-2135	284	5	,	,	PUNCT
fcis-2135	284	6	learn	learn	VERB
fcis-2135	284	7	inductive	inductive	ADJ
fcis-2135	284	8	models	model	NOUN
fcis-2135	284	9	,	,	PUNCT
fcis-2135	284	10	mine	mine	NOUN
fcis-2135	284	11	and	and	CCONJ
fcis-2135	284	12	reason	reason	NOUN
fcis-2135	284	13	pedestrian	pedestrian	NOUN
fcis-2135	284	14	motion	motion	NOUN
fcis-2135	284	15	patterns	pattern	NOUN
fcis-2135	284	16	and	and	CCONJ
fcis-2135	284	17	collision	collision	NOUN
fcis-2135	284	18	avoidance	avoidance	NOUN
fcis-2135	284	19	rules	rule	NOUN
fcis-2135	284	20	and	and	CCONJ
fcis-2135	284	21	norms	norm	NOUN
fcis-2135	284	22	.	.	PUNCT
fcis-2135	285	1	at	at	ADP
fcis-2135	285	2	the	the	DET
fcis-2135	285	3	same	same	ADJ
fcis-2135	285	4	time	time	NOUN
fcis-2135	285	5	,	,	PUNCT
fcis-2135	285	6	the	the	DET
fcis-2135	285	7	prediction	prediction	NOUN
fcis-2135	285	8	and	and	CCONJ
fcis-2135	285	9	control	control	NOUN
fcis-2135	285	10	are	be	AUX
fcis-2135	285	11	combined	combine	VERB
fcis-2135	285	12	to	to	PART
fcis-2135	285	13	improve	improve	VERB
fcis-2135	285	14	the	the	DET
fcis-2135	285	15	overall	overall	ADJ
fcis-2135	285	16	robustness	robustness	NOUN
fcis-2135	285	17	of	of	ADP
fcis-2135	285	18	the	the	DET
fcis-2135	285	19	system	system	NOUN
fcis-2135	285	20	.	.	PUNCT
fcis-2135	286	1	enhance	enhance	VERB
fcis-2135	286	2	context	context	NOUN
fcis-2135	286	3	feature	feature	NOUN
fcis-2135	286	4	analysis	analysis	NOUN
fcis-2135	286	5	and	and	CCONJ
fcis-2135	286	6	deeply	deeply	ADV
fcis-2135	286	7	understand	understand	VERB
fcis-2135	286	8	semantic	semantic	ADJ
fcis-2135	286	9	scenarios	scenario	NOUN
fcis-2135	286	10	.	.	PUNCT
fcis-2135	287	1	the	the	DET
fcis-2135	287	2	combination	combination	NOUN
fcis-2135	287	3	of	of	ADP
fcis-2135	287	4	context	context	NOUN
fcis-2135	287	5	and	and	CCONJ
fcis-2135	287	6	surrounding	surround	VERB
fcis-2135	287	7	environment	environment	NOUN
fcis-2135	287	8	can	can	AUX
fcis-2135	287	9	realize	realize	VERB
fcis-2135	287	10	long	long	ADJ
fcis-2135	287	11	-	-	PUNCT
fcis-2135	287	12	term	term	NOUN
fcis-2135	287	13	prediction	prediction	NOUN
fcis-2135	287	14	and	and	CCONJ
fcis-2135	287	15	help	help	VERB
fcis-2135	287	16	to	to	PART
fcis-2135	287	17	explain	explain	VERB
fcis-2135	287	18	pedestrian	pedestrian	NOUN
fcis-2135	287	19	's	's	PART
fcis-2135	287	20	motion	motion	NOUN
fcis-2135	287	21	intention	intention	NOUN
fcis-2135	287	22	.	.	PUNCT
fcis-2135	288	1	however	however	ADV
fcis-2135	288	2	,	,	PUNCT
fcis-2135	288	3	the	the	DET
fcis-2135	288	4	context	context	NOUN
fcis-2135	288	5	understanding	understanding	NOUN
fcis-2135	288	6	of	of	ADP
fcis-2135	288	7	dynamic	dynamic	ADJ
fcis-2135	288	8	and	and	CCONJ
fcis-2135	288	9	static	static	ADJ
fcis-2135	288	10	environment	environment	NOUN
fcis-2135	288	11	features	feature	NOUN
fcis-2135	288	12	and	and	CCONJ
fcis-2135	288	13	their	their	PRON
fcis-2135	288	14	semantics	semantic	NOUN
fcis-2135	288	15	is	be	AUX
fcis-2135	288	16	still	still	ADV
fcis-2135	288	17	an	an	DET
fcis-2135	288	18	unexplored	unexplored	ADJ
fcis-2135	288	19	field	field	NOUN
fcis-2135	288	20	for	for	ADP
fcis-2135	288	21	better	well	ADJ
fcis-2135	288	22	trajectory	trajectory	NOUN
fcis-2135	288	23	prediction	prediction	NOUN
fcis-2135	288	24	.	.	PUNCT
fcis-2135	289	1	for	for	ADP
fcis-2135	289	2	scene	scene	NOUN
fcis-2135	289	3	understanding	understanding	NOUN
fcis-2135	289	4	,	,	PUNCT
fcis-2135	289	5	it	it	PRON
fcis-2135	289	6	is	be	AUX
fcis-2135	289	7	necessary	necessary	ADJ
fcis-2135	289	8	to	to	PART
fcis-2135	289	9	make	make	VERB
fcis-2135	289	10	full	full	ADJ
fcis-2135	289	11	use	use	NOUN
fcis-2135	289	12	of	of	ADP
fcis-2135	289	13	the	the	DET
fcis-2135	289	14	global	global	ADJ
fcis-2135	289	15	context	context	PROPN
fcis-2135	289	16	information	information	NOUN
fcis-2135	289	17	and	and	CCONJ
fcis-2135	289	18	high	high	ADJ
fcis-2135	289	19	-	-	PUNCT
fcis-2135	289	20	level	level	NOUN
fcis-2135	289	21	semantic	semantic	ADJ
fcis-2135	289	22	features	feature	NOUN
fcis-2135	289	23	to	to	PART
fcis-2135	289	24	describe	describe	VERB
fcis-2135	289	25	the	the	DET
fcis-2135	289	26	scene	scene	NOUN
fcis-2135	289	27	content	content	NOUN
fcis-2135	289	28	for	for	ADP
fcis-2135	289	29	the	the	DET
fcis-2135	289	30	limitations	limitation	NOUN
fcis-2135	289	31	of	of	ADP
fcis-2135	289	32	local	local	ADJ
fcis-2135	289	33	context	context	NOUN
fcis-2135	289	34	and	and	CCONJ
fcis-2135	289	35	other	other	ADJ
fcis-2135	289	36	issues	issue	NOUN
fcis-2135	289	37	.	.	PUNCT
fcis-2135	290	1	expand	expand	VERB
fcis-2135	290	2	access	access	NOUN
fcis-2135	290	3	to	to	ADP
fcis-2135	290	4	data	datum	NOUN
fcis-2135	290	5	and	and	CCONJ
fcis-2135	290	6	enhance	enhance	VERB
fcis-2135	290	7	data	datum	NOUN
fcis-2135	290	8	fusion	fusion	NOUN
fcis-2135	290	9	.	.	PUNCT
fcis-2135	291	1	combined	combine	VERB
fcis-2135	291	2	with	with	ADP
fcis-2135	291	3	the	the	DET
fcis-2135	291	4	functional	functional	ADJ
fcis-2135	291	5	application	application	NOUN
fcis-2135	291	6	of	of	ADP
fcis-2135	291	7	cameras	camera	NOUN
fcis-2135	291	8	,	,	PUNCT
fcis-2135	291	9	laser	laser	NOUN
fcis-2135	291	10	radars	radar	NOUN
fcis-2135	291	11	and	and	CCONJ
fcis-2135	291	12	other	other	ADJ
fcis-2135	291	13	hardware	hardware	NOUN
fcis-2135	291	14	sensors	sensor	NOUN
fcis-2135	291	15	,	,	PUNCT
fcis-2135	291	16	data	datum	NOUN
fcis-2135	291	17	fusion	fusion	NOUN
fcis-2135	291	18	is	be	AUX
fcis-2135	291	19	completed	complete	VERB
fcis-2135	291	20	in	in	ADP
fcis-2135	291	21	cascade	cascade	NOUN
fcis-2135	291	22	.	.	PUNCT
fcis-2135	292	1	through	through	ADP
fcis-2135	292	2	software	software	NOUN
fcis-2135	292	3	recognition	recognition	NOUN
fcis-2135	292	4	algorithm	algorithm	NOUN
fcis-2135	292	5	or	or	CCONJ
fcis-2135	292	6	face	face	NOUN
fcis-2135	292	7	recognition	recognition	NOUN
fcis-2135	292	8	technology	technology	NOUN
fcis-2135	292	9	,	,	PUNCT
fcis-2135	292	10	accurately	accurately	ADV
fcis-2135	292	11	identify	identify	VERB
fcis-2135	292	12	pedestrian	pedestrian	NOUN
fcis-2135	292	13	posture	posture	NOUN
fcis-2135	292	14	,	,	PUNCT
fcis-2135	292	15	judge	judge	VERB
fcis-2135	292	16	the	the	DET
fcis-2135	292	17	subjective	subjective	ADJ
fcis-2135	292	18	intention	intention	NOUN
fcis-2135	292	19	of	of	ADP
fcis-2135	292	20	pedestrians	pedestrian	NOUN
fcis-2135	292	21	,	,	PUNCT
fcis-2135	292	22	and	and	CCONJ
fcis-2135	292	23	enhance	enhance	VERB
fcis-2135	292	24	the	the	DET
fcis-2135	292	25	interpretability	interpretability	NOUN
fcis-2135	292	26	of	of	ADP
fcis-2135	292	27	the	the	DET
fcis-2135	292	28	model	model	NOUN
fcis-2135	292	29	,	,	PUNCT
fcis-2135	292	30	so	so	SCONJ
fcis-2135	292	31	as	as	SCONJ
fcis-2135	292	32	to	to	PART
fcis-2135	292	33	make	make	VERB
fcis-2135	292	34	the	the	DET
fcis-2135	292	35	perception	perception	NOUN
fcis-2135	292	36	and	and	CCONJ
fcis-2135	292	37	decision	decision	NOUN
fcis-2135	292	38	-	-	PUNCT
fcis-2135	292	39	making	making	NOUN
fcis-2135	292	40	of	of	ADP
fcis-2135	292	41	the	the	DET
fcis-2135	292	42	model	model	NOUN
fcis-2135	292	43	more	more	ADV
fcis-2135	292	44	effective	effective	ADJ
fcis-2135	292	45	.	.	PUNCT
fcis-2135	293	1	table	table	NOUN
fcis-2135	293	2	5	5	NUM
fcis-2135	293	3	.	.	PUNCT
fcis-2135	293	4	performance	performance	NOUN
fcis-2135	293	5	of	of	ADP
fcis-2135	293	6	each	each	DET
fcis-2135	293	7	trajectory	trajectory	NOUN
fcis-2135	293	8	prediction	prediction	NOUN
fcis-2135	293	9	method	method	NOUN
fcis-2135	293	10	on	on	ADP
fcis-2135	293	11	eth	eth	PROPN
fcis-2135	293	12	and	and	CCONJ
fcis-2135	293	13	ucy	ucy	PROPN
fcis-2135	293	14	data	datum	NOUN
fcis-2135	293	15	set	set	VERB
fcis-2135	293	16	method	method	NOUN
fcis-2135	293	17	reference	reference	NOUN
fcis-2135	293	18	evaluating	evaluate	VERB
fcis-2135	293	19	indicator	indicator	NOUN
fcis-2135	293	20	(	(	PUNCT
fcis-2135	293	21	ade	ade	PROPN
fcis-2135	293	22	/	/	SYM
fcis-2135	293	23	fde	fde	PROPN
fcis-2135	293	24	)	)	PUNCT
fcis-2135	293	25	eth	eth	PROPN
fcis-2135	293	26	hotel	hotel	PROPN
fcis-2135	293	27	univ	univ	PROPN
fcis-2135	293	28	zara1	zara1	PROPN
fcis-2135	293	29	zara2	zara2	PUNCT
fcis-2135	294	1	average	average	ADJ
fcis-2135	294	2	sophie	sophie	NOUN
fcis-2135	294	3	[	[	X
fcis-2135	294	4	13	13	NUM
fcis-2135	294	5	]	]	SYM
fcis-2135	294	6	0.70/1.44	0.70/1.44	NUM
fcis-2135	294	7	0.76/1.68	0.76/1.68	NUM
fcis-2135	294	8	0.54/1.24	0.54/1.24	NUM
fcis-2135	294	9	0.30/0.64	0.30/0.64	NUM
fcis-2135	294	10	0.38/0.78	0.38/0.78	NUM
fcis-2135	294	11	0.54/1.15	0.54/1.15	NUM
fcis-2135	294	12	s	s	NOUN
fcis-2135	294	13	-	-	VERB
fcis-2135	294	14	lstm	lstm	ADJ
fcis-2135	294	15	[	[	X
fcis-2135	294	16	20	20	NUM
fcis-2135	294	17	]	]	PUNCT
fcis-2135	294	18	1.09/2.35	1.09/2.35	NUM
fcis-2135	294	19	0.79/1.76	0.79/1.76	NUM
fcis-2135	294	20	0.67/1.42	0.67/1.42	NUM
fcis-2135	294	21	0.47/1.02	0.47/1.02	NUM
fcis-2135	294	22	0.56/1.18	0.56/1.18	NUM
fcis-2135	294	23	0.72/1.56	0.72/1.56	NUM
fcis-2135	294	24	sr	sr	PROPN
fcis-2135	294	25	-	-	PUNCT
fcis-2135	294	26	lstm	lstm	PROPN
fcis-2135	295	1	[	[	X
fcis-2135	295	2	22	22	NUM
fcis-2135	295	3	]	]	PUNCT
fcis-2135	295	4	1.05/2.21	1.05/2.21	NUM
fcis-2135	295	5	0.81/1.68	0.81/1.68	NOUN
fcis-2135	295	6	0.71/1.45	0.71/1.45	NUM
fcis-2135	295	7	0.47/1.02	0.47/1.02	NUM
fcis-2135	295	8	0.64/1.25	0.64/1.25	NUM
fcis-2135	295	9	0.74/1.52	0.74/1.52	NUM
fcis-2135	295	10	s	s	NOUN
fcis-2135	295	11	-	-	NOUN
fcis-2135	295	12	attention	attention	NOUN
fcis-2135	296	1	[	[	X
fcis-2135	296	2	41	41	NUM
fcis-2135	296	3	]	]	PUNCT
fcis-2135	296	4	3.62/4.71	3.62/4.71	NUM
fcis-2135	296	5	0.79/1.44	0.79/1.44	NUM
fcis-2135	296	6	1.30/2.66	1.30/2.66	NUM
fcis-2135	296	7	0.95/2.06	0.95/2.06	ADP
fcis-2135	296	8	1.02/2.14	1.02/2.14	NUM
fcis-2135	296	9	1.53/3.53	1.53/3.53	NUM
fcis-2135	296	10	mx	mx	NOUN
fcis-2135	296	11	-	-	NOUN
fcis-2135	296	12	lstm	lstm	NOUN
fcis-2135	296	13	[	[	X
fcis-2135	296	14	42	42	NUM
fcis-2135	296	15	]	]	PUNCT
fcis-2135	296	16	1.05/2.22	1.05/2.22	NUM
fcis-2135	296	17	0.81/1.68	0.81/1.68	NOUN
fcis-2135	296	18	0.71/1.46	0.71/1.46	NUM
fcis-2135	296	19	0.47/1.03	0.47/1.03	NUM
fcis-2135	296	20	0.64/1.26	0.64/1.26	NUM
fcis-2135	296	21	0.74/1.53	0.74/1.53	NUM
fcis-2135	297	1	s	s	X
fcis-2135	297	2	-	-	PUNCT
fcis-2135	297	3	gan	gin	VERB
fcis-2135	298	1	[	[	X
fcis-2135	298	2	28	28	NUM
fcis-2135	298	3	]	]	PUNCT
fcis-2135	298	4	0.82/1.52	0.82/1.52	NUM
fcis-2135	298	5	0.72/1.62	0.72/1.62	NUM
fcis-2135	298	6	0.61/1.25	0.61/1.25	NUM
fcis-2135	298	7	0.34/0.70	0.34/0.70	NUM
fcis-2135	298	8	0.42/0.84	0.42/0.84	NOUN
fcis-2135	298	9	0.58/1.18	0.58/1.18	PRON
fcis-2135	298	10	s	s	NOUN
fcis-2135	298	11	-	-	PUNCT
fcis-2135	298	12	rnn	rnn	VERB
fcis-2135	298	13	[	[	X
fcis-2135	298	14	30	30	NUM
fcis-2135	298	15	]	]	SYM
fcis-2135	298	16	2.72/4.60	2.72/4.60	NUM
fcis-2135	298	17	0.85/1.35	0.85/1.35	NUM
fcis-2135	298	18	1.05/2.23	1.05/2.23	NUM
fcis-2135	298	19	1.61/3.52	1.61/3.52	NUM
fcis-2135	298	20	1.45/3.01	1.45/3.01	NUM
fcis-2135	298	21	1.53/2.94	1.53/2.94	NUM
fcis-2135	298	22	stg	stg	ADJ
fcis-2135	298	23	-	-	PUNCT
fcis-2135	298	24	gan	gan	NOUN
fcis-2135	299	1	[	[	X
fcis-2135	299	2	52	52	NUM
fcis-2135	299	3	]	]	SYM
fcis-2135	299	4	0.64/1.12	0.64/1.12	NUM
fcis-2135	299	5	0.79/0.85	0.79/0.85	NUM
fcis-2135	299	6	0.45/0.78	0.45/0.78	NOUN
fcis-2135	299	7	0.34/0.54	0.34/0.54	NUM
fcis-2135	299	8	0.31/0.48	0.31/0.48	NUM
fcis-2135	299	9	0.44/0.75	0.44/0.75	NUM
fcis-2135	300	1	linear	linear	NOUN
fcis-2135	301	1	[	[	X
fcis-2135	301	2	43	43	NUM
fcis-2135	301	3	]	]	SYM
fcis-2135	301	4	1.33/2.94	1.33/2.94	NUM
fcis-2135	301	5	0.39/0.72	0.39/0.72	NUM
fcis-2135	301	6	0.82/1.59	0.82/1.59	NUM
fcis-2135	301	7	0.62/1.21	0.62/1.21	NUM
fcis-2135	301	8	0.77/1.48	0.77/1.48	NUM
fcis-2135	301	9	0.78/1.57	0.78/1.57	X
fcis-2135	302	1	social	social	ADJ
fcis-2135	302	2	ways	way	NOUN
fcis-2135	302	3	[	[	X
fcis-2135	302	4	55	55	NUM
fcis-2135	302	5	]	]	SYM
fcis-2135	302	6	0.39/0.63	0.39/0.63	NUM
fcis-2135	302	7	0.39/0.66	0.39/0.66	NUM
fcis-2135	302	8	0.55/1.32	0.55/1.32	NUM
fcis-2135	302	9	0.44/0.64	0.44/0.64	NUM
fcis-2135	302	10	0.52/0.94	0.52/0.94	NUM
fcis-2135	302	11	0.46/0.82	0.46/0.82	NUM
fcis-2135	302	12	gat	gat	NOUN
fcis-2135	302	13	[	[	X
fcis-2135	302	14	47	47	NUM
fcis-2135	302	15	]	]	SYM
fcis-2135	302	16	0.68/1.30	0.68/1.30	NUM
fcis-2135	303	1	0.68/1.41	0.68/1.41	NUM
fcis-2135	303	2	0.57/1.31	0.57/1.31	NUM
fcis-2135	303	3	0.29/0.60	0.29/0.60	NUM
fcis-2135	304	1	0.37/0.76	0.37/0.76	NUM
fcis-2135	304	2	0.52/1.08	0.52/1.08	NUM
fcis-2135	304	3	socialbigat	socialbigat	NOUN
fcis-2135	304	4	[	[	X
fcis-2135	304	5	51	51	NUM
fcis-2135	304	6	]	]	PUNCT
fcis-2135	304	7	0.69/1.31	0.69/1.31	NUM
fcis-2135	304	8	0.49/1.02	0.49/1.02	NUM
fcis-2135	304	9	0.55/1.33	0.55/1.33	NUM
fcis-2135	304	10	0.31/0.62	0.31/0.62	NUM
fcis-2135	304	11	0.36/0.75	0.36/0.75	NUM
fcis-2135	304	12	0.48/1.02	0.48/1.02	NUM
fcis-2135	304	13	stgat	stgat	NOUN
fcis-2135	304	14	[	[	X
fcis-2135	304	15	54	54	NUM
fcis-2135	304	16	]	]	SYM
fcis-2135	304	17	0.71/1.36	0.71/1.36	NUM
fcis-2135	304	18	0.37/0.65	0.37/0.65	NUM
fcis-2135	304	19	0.59/1.23	0.59/1.23	NUM
fcis-2135	304	20	0.35/0.69	0.35/0.69	NUM
fcis-2135	304	21	0.32/0.66	0.32/0.66	NUM
fcis-2135	304	22	0.47/0.95	0.47/0.95	NOUN
fcis-2135	304	23	tppo	tppo	NOUN
fcis-2135	305	1	[	[	X
fcis-2135	305	2	56	56	NUM
fcis-2135	305	3	]	]	PUNCT
fcis-2135	305	4	0.84/1.74	0.84/1.74	NUM
fcis-2135	305	5	0.24/0.47	0.24/0.47	NUM
fcis-2135	305	6	0.42/0.95	0.42/0.95	NUM
fcis-2135	306	1	0.34/0.76	0.34/0.76	NUM
fcis-2135	306	2	0.26/0.61	0.26/0.61	NUM
fcis-2135	306	3	0.42/0.90	0.42/0.90	NOUN
fcis-2135	306	4	next	next	ADJ
fcis-2135	307	1	[	[	X
fcis-2135	307	2	60	60	NUM
fcis-2135	307	3	]	]	SYM
fcis-2135	307	4	0.64/1.12	0.64/1.12	NUM
fcis-2135	307	5	0.79/0.86	0.79/0.86	NUM
fcis-2135	307	6	0.44/0.78	0.44/0.78	SYM
fcis-2135	307	7	0.34/0.53	0.34/0.53	NUM
fcis-2135	307	8	0.31/0.48	0.31/0.48	NUM
fcis-2135	307	9	0.44/0.76	0.44/0.76	NUM
fcis-2135	307	10	6	6	NUM
fcis-2135	307	11	.	.	PUNCT
fcis-2135	307	12	conclusion	conclusion	NOUN
fcis-2135	307	13	in	in	ADP
fcis-2135	307	14	recent	recent	ADJ
fcis-2135	307	15	years	year	NOUN
fcis-2135	307	16	,	,	PUNCT
fcis-2135	307	17	with	with	ADP
fcis-2135	307	18	the	the	DET
fcis-2135	307	19	progress	progress	NOUN
fcis-2135	307	20	of	of	ADP
fcis-2135	307	21	science	science	NOUN
fcis-2135	307	22	and	and	CCONJ
fcis-2135	307	23	technology	technology	NOUN
fcis-2135	307	24	,	,	PUNCT
fcis-2135	307	25	the	the	DET
fcis-2135	307	26	research	research	NOUN
fcis-2135	307	27	of	of	ADP
fcis-2135	307	28	pedestrian	pedestrian	NOUN
fcis-2135	307	29	trajectory	trajectory	NOUN
fcis-2135	307	30	prediction	prediction	NOUN
fcis-2135	307	31	based	base	VERB
fcis-2135	307	32	on	on	ADP
fcis-2135	307	33	deep	deep	ADJ
fcis-2135	307	34	learning	learning	NOUN
fcis-2135	307	35	has	have	AUX
fcis-2135	307	36	made	make	VERB
fcis-2135	307	37	significant	significant	ADJ
fcis-2135	307	38	progress	progress	NOUN
fcis-2135	307	39	.	.	PUNCT
fcis-2135	308	1	however	however	ADV
fcis-2135	308	2	,	,	PUNCT
fcis-2135	308	3	due	due	ADP
fcis-2135	308	4	to	to	ADP
fcis-2135	308	5	the	the	DET
fcis-2135	308	6	complexity	complexity	NOUN
fcis-2135	308	7	and	and	CCONJ
fcis-2135	308	8	uncertainty	uncertainty	NOUN
fcis-2135	308	9	of	of	ADP
fcis-2135	308	10	the	the	DET
fcis-2135	308	11	interaction	interaction	NOUN
fcis-2135	308	12	between	between	ADP
fcis-2135	308	13	pedestrians	pedestrian	NOUN
fcis-2135	308	14	,	,	PUNCT
fcis-2135	308	15	pedestrians	pedestrian	NOUN
fcis-2135	308	16	and	and	CCONJ
fcis-2135	308	17	the	the	DET
fcis-2135	308	18	environment	environment	NOUN
fcis-2135	308	19	,	,	PUNCT
fcis-2135	308	20	pedestrian	pedestrian	NOUN
fcis-2135	308	21	trajectory	trajectory	NOUN
fcis-2135	308	22	prediction	prediction	NOUN
fcis-2135	308	23	still	still	ADV
fcis-2135	308	24	has	have	VERB
fcis-2135	308	25	some	some	DET
fcis-2135	308	26	problems	problem	NOUN
fcis-2135	308	27	and	and	CCONJ
fcis-2135	308	28	challenges	challenge	NOUN
fcis-2135	308	29	.	.	PUNCT
fcis-2135	309	1	starting	start	VERB
fcis-2135	309	2	from	from	ADP
fcis-2135	309	3	the	the	DET
fcis-2135	309	4	essence	essence	NOUN
fcis-2135	309	5	and	and	CCONJ
fcis-2135	309	6	challenges	challenge	NOUN
fcis-2135	309	7	of	of	ADP
fcis-2135	309	8	trajectory	trajectory	NOUN
fcis-2135	309	9	prediction	prediction	NOUN
fcis-2135	309	10	,	,	PUNCT
fcis-2135	309	11	this	this	DET
fcis-2135	309	12	paper	paper	NOUN
fcis-2135	309	13	summarizes	summarize	VERB
fcis-2135	309	14	the	the	DET
fcis-2135	309	15	work	work	NOUN
fcis-2135	309	16	in	in	ADP
fcis-2135	309	17	the	the	DET
fcis-2135	309	18	field	field	NOUN
fcis-2135	309	19	of	of	ADP
fcis-2135	309	20	trajectory	trajectory	NOUN
fcis-2135	309	21	prediction	prediction	NOUN
fcis-2135	309	22	this	this	DET
fcis-2135	309	23	year	year	NOUN
fcis-2135	309	24	,	,	PUNCT
fcis-2135	309	25	classifies	classify	VERB
fcis-2135	309	26	the	the	DET
fcis-2135	309	27	current	current	ADJ
fcis-2135	309	28	pedestrian	pedestrian	NOUN
fcis-2135	309	29	trajectory	trajectory	NOUN
fcis-2135	309	30	prediction	prediction	NOUN
fcis-2135	309	31	methods	method	NOUN
fcis-2135	309	32	based	base	VERB
fcis-2135	309	33	on	on	ADP
fcis-2135	309	34	the	the	DET
fcis-2135	309	35	structural	structural	ADJ
fcis-2135	309	36	design	design	NOUN
fcis-2135	309	37	and	and	CCONJ
fcis-2135	309	38	optimization	optimization	NOUN
fcis-2135	309	39	of	of	ADP
fcis-2135	309	40	models	model	NOUN
fcis-2135	309	41	,	,	PUNCT
fcis-2135	309	42	and	and	CCONJ
fcis-2135	309	43	summarizes	summarize	VERB
fcis-2135	309	44	the	the	DET
fcis-2135	309	45	advantages	advantage	NOUN
fcis-2135	309	46	and	and	CCONJ
fcis-2135	309	47	disadvantages	disadvantage	NOUN
fcis-2135	309	48	of	of	ADP
fcis-2135	309	49	different	different	ADJ
fcis-2135	309	50	algorithms	algorithm	NOUN
fcis-2135	309	51	.	.	PUNCT
fcis-2135	310	1	the	the	DET
fcis-2135	310	2	research	research	NOUN
fcis-2135	310	3	of	of	ADP
fcis-2135	310	4	pedestrian	pedestrian	NOUN
fcis-2135	310	5	trajectory	trajectory	NOUN
fcis-2135	310	6	prediction	prediction	NOUN
fcis-2135	310	7	involves	involve	VERB
fcis-2135	310	8	many	many	ADJ
fcis-2135	310	9	fields	field	NOUN
fcis-2135	310	10	,	,	PUNCT
fcis-2135	310	11	such	such	ADJ
fcis-2135	310	12	as	as	ADP
fcis-2135	310	13	automatic	automatic	ADJ
fcis-2135	310	14	driving	driving	NOUN
fcis-2135	310	15	,	,	PUNCT
fcis-2135	310	16	behavior	behavior	NOUN
fcis-2135	310	17	recognition	recognition	NOUN
fcis-2135	310	18	,	,	PUNCT
fcis-2135	310	19	target	target	NOUN
fcis-2135	310	20	detection	detection	NOUN
fcis-2135	310	21	and	and	CCONJ
fcis-2135	310	22	tracking	tracking	NOUN
fcis-2135	310	23	,	,	PUNCT
fcis-2135	310	24	etc	etc	X
fcis-2135	310	25	.	.	X
fcis-2135	311	1	it	it	PRON
fcis-2135	311	2	is	be	AUX
fcis-2135	311	3	not	not	PART
fcis-2135	311	4	only	only	ADV
fcis-2135	311	5	a	a	DET
fcis-2135	311	6	major	major	ADJ
fcis-2135	311	7	challenge	challenge	NOUN
fcis-2135	311	8	in	in	ADP
fcis-2135	311	9	the	the	DET
fcis-2135	311	10	field	field	NOUN
fcis-2135	311	11	of	of	ADP
fcis-2135	311	12	computer	computer	NOUN
fcis-2135	311	13	vision	vision	NOUN
fcis-2135	311	14	,	,	PUNCT
fcis-2135	311	15	but	but	CCONJ
fcis-2135	311	16	also	also	ADV
fcis-2135	311	17	plays	play	VERB
fcis-2135	311	18	a	a	DET
fcis-2135	311	19	significant	significant	ADJ
fcis-2135	311	20	role	role	NOUN
fcis-2135	311	21	in	in	ADP
fcis-2135	311	22	the	the	DET
fcis-2135	311	23	development	development	NOUN
fcis-2135	311	24	of	of	ADP
fcis-2135	311	25	artificial	artificial	ADJ
fcis-2135	311	26	intelligence	intelligence	NOUN
fcis-2135	311	27	.	.	PUNCT
fcis-2135	312	1	references	reference	NOUN
fcis-2135	312	2	[	[	X
fcis-2135	312	3	1	1	NUM
fcis-2135	312	4	]	]	X
fcis-2135	312	5	wang	wang	PROPN
fcis-2135	312	6	,	,	PUNCT
fcis-2135	312	7	jinxiang	jinxiang	PROPN
fcis-2135	312	8	,	,	PUNCT
fcis-2135	312	9	dai	dai	PROPN
fcis-2135	312	10	,	,	PUNCT
fcis-2135	312	11	et	et	PROPN
fcis-2135	312	12	al	al	PROPN
fcis-2135	312	13	.	.	PROPN
fcis-2135	312	14	output	output	NOUN
fcis-2135	312	15	-	-	PUNCT
fcis-2135	312	16	feedback	feedback	NOUN
fcis-2135	312	17	robust	robust	ADJ
fcis-2135	312	18	control	control	NOUN
fcis-2135	312	19	for	for	ADP
fcis-2135	312	20	vehicle	vehicle	NOUN
fcis-2135	312	21	path	path	NOUN
fcis-2135	312	22	tracking	tracking	NOUN
fcis-2135	312	23	considering	consider	VERB
fcis-2135	312	24	different	different	ADJ
fcis-2135	312	25	human	human	ADJ
fcis-2135	312	26	drivers	driver	NOUN
fcis-2135	312	27	'	'	PART
fcis-2135	312	28	characteristics[j	characteristics[j	PROPN
fcis-2135	312	29	]	]	PUNCT
fcis-2135	312	30	.	.	PUNCT
fcis-2135	313	1	mechatronics	mechatronic	NOUN
fcis-2135	313	2	:	:	PUNCT
fcis-2135	313	3	the	the	DET
fcis-2135	313	4	science	science	NOUN
fcis-2135	313	5	of	of	ADP
fcis-2135	313	6	intelligent	intelligent	ADJ
fcis-2135	313	7	machines	machine	NOUN
fcis-2135	313	8	,	,	PUNCT
fcis-2135	313	9	2018	2018	NUM
fcis-2135	313	10	,	,	PUNCT
fcis-2135	313	11	50:402	50:402	NUM
fcis-2135	313	12	-	-	SYM
fcis-2135	313	13	412	412	NUM
fcis-2135	313	14	.	.	PUNCT
fcis-2135	314	1	[	[	X
fcis-2135	314	2	2	2	NUM
fcis-2135	314	3	]	]	X
fcis-2135	314	4	moussaid	moussaid	VERB
fcis-2135	314	5	m	m	PROPN
fcis-2135	314	6	,	,	PUNCT
fcis-2135	314	7	perozo	perozo	PROPN
fcis-2135	314	8	n	n	CCONJ
fcis-2135	314	9	,	,	PUNCT
fcis-2135	314	10	garnier	garnier	PROPN
fcis-2135	314	11	s	s	PROPN
fcis-2135	314	12	,	,	PUNCT
fcis-2135	314	13	et	et	PROPN
fcis-2135	314	14	al	al	PROPN
fcis-2135	314	15	.	.	PUNCT
fcis-2135	315	1	the	the	DET
fcis-2135	315	2	walking	walk	VERB
fcis-2135	315	3	behaviour	behaviour	NOUN
fcis-2135	315	4	of	of	ADP
fcis-2135	315	5	pedestrian	pedestrian	NOUN
fcis-2135	315	6	social	social	ADJ
fcis-2135	315	7	groups	group	NOUN
fcis-2135	315	8	and	and	CCONJ
fcis-2135	315	9	its	its	PRON
fcis-2135	315	10	impact	impact	NOUN
fcis-2135	315	11	on	on	ADP
fcis-2135	315	12	crowd	crowd	NOUN
fcis-2135	315	13	dynamics[j	dynamics[j	NOUN
fcis-2135	315	14	]	]	PUNCT
fcis-2135	315	15	.	.	PUNCT
fcis-2135	316	1	plos	plos	PROPN
fcis-2135	316	2	one	one	NUM
fcis-2135	316	3	,	,	PUNCT
fcis-2135	316	4	2010	2010	NUM
fcis-2135	316	5	,	,	PUNCT
fcis-2135	316	6	5(4	5(4	NUM
fcis-2135	316	7	):	):	PUNCT
fcis-2135	316	8	e10047	e10047	ADJ
fcis-2135	316	9	.	.	PUNCT
fcis-2135	317	1	[	[	X
fcis-2135	317	2	3	3	X
fcis-2135	317	3	]	]	X
fcis-2135	317	4	lefevre	lefevre	PROPN
fcis-2135	317	5	s	s	PROPN
fcis-2135	317	6	,	,	PUNCT
fcis-2135	317	7	vasquez	vasquez	PROPN
fcis-2135	317	8	d	d	NOUN
fcis-2135	317	9	,	,	PUNCT
fcis-2135	317	10	laugier	laugi	ADJ
fcis-2135	317	11	c.	c.	NOUN
fcis-2135	317	12	a	a	DET
fcis-2135	317	13	survey	survey	NOUN
fcis-2135	317	14	on	on	ADP
fcis-2135	317	15	motionprediction	motionprediction	NOUN
fcis-2135	317	16	and	and	CCONJ
fcis-2135	317	17	risk	risk	NOUN
fcis-2135	317	18	assessment	assessment	NOUN
fcis-2135	317	19	for	for	ADP
fcis-2135	317	20	intelligent	intelligent	ADJ
fcis-2135	317	21	vehicles[j	vehicles[j	NOUN
fcis-2135	317	22	]	]	PUNCT
fcis-2135	317	23	.	.	PUNCT
fcis-2135	318	1	robomech	robomech	PROPN
fcis-2135	318	2	journal	journal	PROPN
fcis-2135	318	3	,	,	PUNCT
fcis-2135	318	4	2014	2014	NUM
fcis-2135	318	5	,	,	PUNCT
fcis-2135	318	6	1(1	1(1	NUM
fcis-2135	318	7	):	):	PUNCT
fcis-2135	318	8	1	1	NUM
fcis-2135	318	9	-	-	SYM
fcis-2135	318	10	14	14	NUM
fcis-2135	318	11	.	.	PUNCT
fcis-2135	318	12	76	76	NUM
fcis-2135	319	1	[	[	X
fcis-2135	319	2	4	4	NUM
fcis-2135	319	3	]	]	SYM
fcis-2135	319	4	su	su	PROPN
fcis-2135	319	5	lumin	lumin	PROPN
fcis-2135	319	6	research	research	PROPN
fcis-2135	319	7	on	on	ADP
fcis-2135	319	8	trajectory	trajectory	NOUN
fcis-2135	319	9	prediction	prediction	NOUN
fcis-2135	319	10	method	method	NOUN
fcis-2135	319	11	based	base	VERB
fcis-2135	319	12	on	on	ADP
fcis-2135	319	13	machine	machine	NOUN
fcis-2135	319	14	learning	learn	VERB
fcis-2135	319	15	[	[	X
fcis-2135	319	16	d	d	X
fcis-2135	319	17	]	]	X
fcis-2135	319	18	beijing	beijing	PROPN
fcis-2135	319	19	:	:	PUNCT
fcis-2135	319	20	beijing	beijing	PROPN
fcis-2135	319	21	university	university	PROPN
fcis-2135	319	22	of	of	ADP
fcis-2135	319	23	posts	post	NOUN
fcis-2135	319	24	and	and	CCONJ
fcis-2135	319	25	telecommunications	telecommunication	NOUN
fcis-2135	319	26	,	,	PUNCT
fcis-2135	319	27	2019	2019	NUM
fcis-2135	319	28	:	:	PUNCT
fcis-2135	319	29	1	1	NUM
fcis-2135	319	30	-	-	SYM
fcis-2135	319	31	65	65	NUM
fcis-2135	319	32	.	.	PUNCT
fcis-2135	320	1	[	[	X
fcis-2135	320	2	5	5	X
fcis-2135	320	3	]	]	PUNCT
fcis-2135	320	4	helbing	helbe	VERB
fcis-2135	320	5	d	d	PROPN
fcis-2135	320	6	,	,	PUNCT
fcis-2135	320	7	molna	molna	PROPN
fcis-2135	320	8	ŕ	ŕ	NOUN
fcis-2135	320	9	p.	p.	PROPN
fcis-2135	320	10	social	social	ADJ
fcis-2135	320	11	force	force	NOUN
fcis-2135	320	12	model	model	NOUN
fcis-2135	320	13	for	for	ADP
fcis-2135	320	14	pedestrian	pedestrian	NOUN
fcis-2135	320	15	dynamics[j	dynamics[j	PROPN
fcis-2135	320	16	]	]	PUNCT
fcis-2135	320	17	.	.	PUNCT
fcis-2135	321	1	physical	physical	ADJ
fcis-2135	321	2	review	review	PROPN
fcis-2135	321	3	e	e	NOUN
fcis-2135	321	4	,	,	PUNCT
fcis-2135	321	5	1995	1995	NUM
fcis-2135	321	6	,	,	PUNCT
fcis-2135	321	7	51(5	51(5	NUM
fcis-2135	321	8	):	):	PUNCT
fcis-2135	321	9	4282	4282	NUM
fcis-2135	321	10	-	-	SYM
fcis-2135	321	11	4286	4286	NUM
fcis-2135	321	12	.	.	PUNCT
fcis-2135	322	1	[	[	X
fcis-2135	322	2	6	6	NUM
fcis-2135	322	3	]	]	PUNCT
fcis-2135	322	4	ferrer	ferrer	PROPN
fcis-2135	322	5	g	g	PROPN
fcis-2135	322	6	,	,	PUNCT
fcis-2135	322	7	sanfeliu	sanfeliu	ADJ
fcis-2135	322	8	a.	a.	NOUN
fcis-2135	322	9	behavior	behavior	PROPN
fcis-2135	322	10	estimation	estimation	NOUN
fcis-2135	322	11	for	for	ADP
fcis-2135	322	12	a	a	DET
fcis-2135	322	13	complete	complete	ADJ
fcis-2135	322	14	framework	framework	NOUN
fcis-2135	322	15	for	for	ADP
fcis-2135	322	16	human	human	ADJ
fcis-2135	322	17	motion	motion	NOUN
fcis-2135	322	18	prediction	prediction	NOUN
fcis-2135	322	19	in	in	ADP
fcis-2135	322	20	crowded	crowded	ADJ
fcis-2135	322	21	environments[c	environments[c	PROPN
fcis-2135	322	22	]	]	PUNCT
fcis-2135	322	23	.	.	PUNCT
fcis-2135	323	1	proceedings	proceeding	NOUN
fcis-2135	323	2	of	of	ADP
fcis-2135	323	3	the	the	DET
fcis-2135	323	4	ieee	ieee	NOUN
fcis-2135	323	5	international	international	PROPN
fcis-2135	323	6	conference	conference	NOUN
fcis-2135	323	7	on	on	ADP
fcis-2135	323	8	robotics	robotic	NOUN
fcis-2135	323	9	and	and	CCONJ
fcis-2135	323	10	automation	automation	NOUN
fcis-2135	323	11	.	.	PUNCT
fcis-2135	324	1	hong	hong	PROPN
fcis-2135	324	2	kong	kong	PROPN
fcis-2135	324	3	:	:	PUNCT
fcis-2135	324	4	ieee	ieee	NOUN
fcis-2135	324	5	,	,	PUNCT
fcis-2135	324	6	2014	2014	NUM
fcis-2135	324	7	:	:	PUNCT
fcis-2135	324	8	5940	5940	NUM
fcis-2135	324	9	-	-	SYM
fcis-2135	324	10	5945	5945	NUM
fcis-2135	324	11	.	.	PUNCT
fcis-2135	325	1	[	[	X
fcis-2135	325	2	7	7	X
fcis-2135	325	3	]	]	X
fcis-2135	325	4	yan	yan	PROPN
fcis-2135	326	1	x	x	X
fcis-2135	326	2	,	,	PUNCT
fcis-2135	326	3	kakadiaris	kakadiaris	VERB
fcis-2135	326	4	i	i	PRON
fcis-2135	326	5	a	a	X
fcis-2135	326	6	,	,	PUNCT
fcis-2135	326	7	shah	shah	PROPN
fcis-2135	326	8	s	s	PROPN
fcis-2135	326	9	k.	k.	PROPN
fcis-2135	326	10	modeling	model	VERB
fcis-2135	326	11	local	local	ADJ
fcis-2135	326	12	behavior	behavior	NOUN
fcis-2135	326	13	for	for	ADP
fcis-2135	326	14	predicting	predict	VERB
fcis-2135	326	15	social	social	ADJ
fcis-2135	326	16	interactions	interaction	NOUN
fcis-2135	326	17	towards	towards	ADP
fcis-2135	326	18	human	human	ADJ
fcis-2135	326	19	tracking[j	tracking[j	NOUN
fcis-2135	326	20	]	]	PUNCT
fcis-2135	326	21	.	.	PUNCT
fcis-2135	327	1	pattern	pattern	NOUN
fcis-2135	327	2	recognition	recognition	PROPN
fcis-2135	327	3	,	,	PUNCT
fcis-2135	327	4	2014	2014	NUM
fcis-2135	327	5	,	,	PUNCT
fcis-2135	327	6	47(4	47(4	NUM
fcis-2135	327	7	):	):	PUNCT
fcis-2135	327	8	1626	1626	NUM
fcis-2135	327	9	-	-	SYM
fcis-2135	327	10	1641	1641	NUM
fcis-2135	327	11	.	.	PUNCT
fcis-2135	328	1	[	[	X
fcis-2135	328	2	8	8	NUM
fcis-2135	328	3	]	]	PUNCT
fcis-2135	328	4	ye	ye	NUM
fcis-2135	328	5	h	h	NOUN
fcis-2135	328	6	r	r	NOUN
fcis-2135	328	7	,	,	PUNCT
fcis-2135	328	8	liu	liu	PROPN
fcis-2135	328	9	m	m	PROPN
fcis-2135	328	10	y	y	PROPN
fcis-2135	328	11	,	,	PUNCT
fcis-2135	328	12	zheng	zheng	PROPN
fcis-2135	328	13	w	w	PROPN
fcis-2135	328	14	s	s	PROPN
fcis-2135	328	15	,	,	PUNCT
fcis-2135	328	16	et	et	PROPN
fcis-2135	328	17	al	al	PROPN
fcis-2135	328	18	.	.	PROPN
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fcis-2135	329	2	prediction	prediction	NOUN
fcis-2135	329	3	for	for	ADP
fcis-2135	329	4	multi	multi	ADJ
fcis-2135	329	5	-	-	ADJ
fcis-2135	329	6	class	class	ADJ
fcis-2135	329	7	target	target	NOUN
fcis-2135	329	8	based	base	VERB
fcis-2135	329	9	on	on	ADP
fcis-2135	329	10	preferred	preferred	ADJ
fcis-2135	329	11	speed[j	speed[j	NOUN
fcis-2135	329	12	]	]	PUNCT
fcis-2135	329	13	.	.	PUNCT
fcis-2135	330	1	journal	journal	PROPN
fcis-2135	330	2	of	of	ADP
fcis-2135	330	3	huazhong	huazhong	PROPN
fcis-2135	330	4	university	university	PROPN
fcis-2135	330	5	of	of	ADP
fcis-2135	330	6	science	science	NOUN
fcis-2135	330	7	and	and	CCONJ
fcis-2135	330	8	technology	technology	NOUN
fcis-2135	330	9	:	:	PUNCT
fcis-2135	330	10	natural	natural	ADJ
fcis-2135	330	11	science	science	NOUN
fcis-2135	330	12	edition	edition	NOUN
fcis-2135	330	13	,	,	PUNCT
fcis-2135	330	14	2017	2017	NUM
fcis-2135	330	15	,	,	PUNCT
fcis-2135	330	16	45(10	45(10	NUM
fcis-2135	330	17	):	):	PUNCT
fcis-2135	330	18	100	100	NUM
fcis-2135	330	19	-	-	SYM
fcis-2135	330	20	104	104	NUM
fcis-2135	330	21	.	.	PUNCT
fcis-2135	331	1	[	[	X
fcis-2135	331	2	9	9	NUM
fcis-2135	331	3	]	]	X
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fcis-2135	331	5	n	n	CCONJ
fcis-2135	331	6	,	,	PUNCT
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fcis-2135	331	11	path	path	NOUN
fcis-2135	331	12	prediction	prediction	NOUN
fcis-2135	331	13	with	with	ADP
fcis-2135	331	14	recursive	recursive	ADJ
fcis-2135	331	15	bayesian	bayesian	NOUN
fcis-2135	331	16	filters	filter	NOUN
fcis-2135	331	17	:	:	PUNCT
fcis-2135	331	18	a	a	DET
fcis-2135	331	19	comparative	comparative	ADJ
fcis-2135	331	20	study[c].proceedings	study[c].proceeding	NOUN
fcis-2135	331	21	of	of	ADP
fcis-2135	331	22	the	the	DET
fcis-2135	331	23	german	german	ADJ
fcis-2135	331	24	conference	conference	NOUN
fcis-2135	331	25	on	on	ADP
fcis-2135	331	26	pattern	pattern	NOUN
fcis-2135	331	27	recognition	recognition	NOUN
fcis-2135	331	28	.	.	PUNCT
fcis-2135	332	1	saarbrucken	saarbrucken	VERB
fcis-2135	332	2	:	:	PUNCT
fcis-2135	332	3	springer	springer	NOUN
fcis-2135	332	4	,	,	PUNCT
fcis-2135	332	5	2013	2013	NUM
fcis-2135	332	6	:	:	PUNCT
fcis-2135	332	7	174	174	NUM
fcis-2135	332	8	-	-	SYM
fcis-2135	332	9	183	183	NUM
fcis-2135	332	10	.	.	PUNCT
fcis-2135	333	1	[	[	X
fcis-2135	333	2	10	10	NUM
fcis-2135	333	3	]	]	X
fcis-2135	333	4	schulz	schulz	PROPN
fcis-2135	333	5	a	a	DET
fcis-2135	333	6	t	t	PROPN
fcis-2135	333	7	,	,	PUNCT
fcis-2135	333	8	stiefelhagen	stiefelhagen	PROPN
fcis-2135	333	9	r.	r.	PROPN
fcis-2135	333	10	a	a	DET
fcis-2135	333	11	controlled	control	VERB
fcis-2135	333	12	interactive	interactive	ADJ
fcis-2135	333	13	multiple	multiple	ADJ
fcis-2135	333	14	model	model	NOUN
fcis-2135	333	15	filter	filter	NOUN
fcis-2135	333	16	for	for	ADP
fcis-2135	333	17	combined	combined	ADJ
fcis-2135	333	18	pedestrian	pedestrian	NOUN
fcis-2135	333	19	intention	intention	NOUN
fcis-2135	333	20	recognition	recognition	NOUN
fcis-2135	333	21	and	and	CCONJ
fcis-2135	333	22	path	path	NOUN
fcis-2135	333	23	prediction[c	prediction[c	PROPN
fcis-2135	333	24	]	]	PUNCT
fcis-2135	333	25	.	.	PUNCT
fcis-2135	334	1	proceedings	proceeding	NOUN
fcis-2135	334	2	of	of	ADP
fcis-2135	334	3	the	the	DET
fcis-2135	334	4	ieee	ieee	NOUN
fcis-2135	334	5	international	international	PROPN
fcis-2135	334	6	conference	conference	NOUN
fcis-2135	334	7	on	on	ADP
fcis-2135	334	8	intelligent	intelligent	ADJ
fcis-2135	334	9	transportation	transportation	NOUN
fcis-2135	334	10	systems	system	NOUN
fcis-2135	334	11	.	.	PUNCT
fcis-2135	335	1	gran	gran	PROPN
fcis-2135	335	2	canaria	canaria	PROPN
fcis-2135	335	3	:	:	PUNCT
fcis-2135	335	4	ieee	ieee	NOUN
fcis-2135	335	5	,	,	PUNCT
fcis-2135	335	6	2015	2015	NUM
fcis-2135	335	7	:	:	PUNCT
fcis-2135	335	8	173	173	NUM
fcis-2135	335	9	-	-	SYM
fcis-2135	335	10	178	178	NUM
fcis-2135	335	11	.	.	PUNCT
fcis-2135	336	1	[	[	X
fcis-2135	336	2	11	11	NUM
fcis-2135	336	3	]	]	X
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fcis-2135	337	2	,	,	PUNCT
fcis-2135	337	3	hsu	hsu	PROPN
fcis-2135	337	4	d	d	PROPN
fcis-2135	337	5	,	,	PUNCT
fcis-2135	338	1	et	et	PROPN
fcis-2135	338	2	al	al	PROPN
fcis-2135	338	3	.	.	PUNCT
fcis-2135	338	4	gamma	gamma	PROPN
fcis-2135	338	5	:	:	PUNCT
fcis-2135	338	6	a	a	DET
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fcis-2135	338	8	agent	agent	NOUN
fcis-2135	338	9	motion	motion	NOUN
fcis-2135	338	10	prediction	prediction	NOUN
fcis-2135	338	11	model	model	NOUN
fcis-2135	338	12	for	for	ADP
fcis-2135	338	13	autonomous	autonomous	ADJ
fcis-2135	338	14	driving[j	driving[j	NOUN
fcis-2135	338	15	]	]	PUNCT
fcis-2135	338	16	.	.	PUNCT
fcis-2135	339	1	arxiv	arxiv	PROPN
fcis-2135	339	2	preprint	preprint	VERB
fcis-2135	339	3	arxiv:1906.01566	arxiv:1906.01566	PROPN
fcis-2135	339	4	,	,	PUNCT
fcis-2135	339	5	2019	2019	NUM
fcis-2135	339	6	.	.	PUNCT
fcis-2135	340	1	[	[	X
fcis-2135	340	2	12	12	NUM
fcis-2135	340	3	]	]	X
fcis-2135	340	4	chen	chen	PROPN
fcis-2135	340	5	y	y	PROPN
fcis-2135	340	6	f	f	PROPN
fcis-2135	340	7	,	,	PUNCT
fcis-2135	340	8	liu	liu	PROPN
fcis-2135	340	9	m	m	PROPN
fcis-2135	340	10	,	,	PUNCT
fcis-2135	340	11	everett	everett	PROPN
fcis-2135	340	12	m	m	PROPN
fcis-2135	340	13	,	,	PUNCT
fcis-2135	340	14	et	et	PROPN
fcis-2135	340	15	al	al	PROPN
fcis-2135	340	16	.	.	PROPN
fcis-2135	340	17	decentralized	decentralize	VERB
fcis-2135	340	18	noncommunicating	noncommunicate	VERB
fcis-2135	340	19	multiagent	multiagent	NOUN
fcis-2135	340	20	collision	collision	NOUN
fcis-2135	340	21	avoidance	avoidance	NOUN
fcis-2135	340	22	with	with	ADP
fcis-2135	340	23	deep	deep	ADJ
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fcis-2135	340	25	learning[c	learning[c	NOUN
fcis-2135	340	26	]	]	PUNCT
fcis-2135	340	27	.	.	PUNCT
fcis-2135	341	1	proceedings	proceeding	NOUN
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fcis-2135	341	4	ieee	ieee	NOUN
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fcis-2135	341	6	conference	conference	NOUN
fcis-2135	341	7	on	on	ADP
fcis-2135	341	8	robotics	robotic	NOUN
fcis-2135	341	9	and	and	CCONJ
fcis-2135	341	10	automation	automation	NOUN
fcis-2135	341	11	.	.	PUNCT
fcis-2135	342	1	singapore	singapore	PROPN
fcis-2135	342	2	:	:	PUNCT
fcis-2135	342	3	ieee	ieee	NOUN
fcis-2135	342	4	,	,	PUNCT
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fcis-2135	342	6	:	:	PUNCT
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fcis-2135	342	8	-	-	SYM
fcis-2135	342	9	292	292	NUM
fcis-2135	342	10	.	.	PUNCT
fcis-2135	343	1	[	[	X
fcis-2135	343	2	13	13	NUM
fcis-2135	343	3	]	]	SYM
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fcis-2135	343	11	a	a	NOUN
fcis-2135	343	12	,	,	PUNCT
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fcis-2135	343	14	al	al	PROPN
fcis-2135	343	15	.	.	PROPN
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fcis-2135	343	17	:	:	PUNCT
fcis-2135	343	18	an	an	DET
fcis-2135	343	19	attentive	attentive	ADJ
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fcis-2135	343	25	to	to	ADP
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fcis-2135	343	28	physical	physical	ADJ
fcis-2135	343	29	constraints[c	constraints[c	PROPN
fcis-2135	343	30	]	]	PUNCT
fcis-2135	343	31	.	.	PUNCT
fcis-2135	344	1	proceedings	proceeding	NOUN
fcis-2135	344	2	of	of	ADP
fcis-2135	344	3	the	the	DET
fcis-2135	344	4	ieee	ieee	NOUN
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fcis-2135	344	7	computer	computer	NOUN
fcis-2135	344	8	vision	vision	NOUN
fcis-2135	344	9	and	and	CCONJ
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fcis-2135	344	11	recognition	recognition	NOUN
fcis-2135	344	12	.	.	PUNCT
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fcis-2135	345	2	beach	beach	NOUN
fcis-2135	345	3	:	:	PUNCT
fcis-2135	345	4	ieee	ieee	PROPN
fcis-2135	345	5	cs	cs	PROPN
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fcis-2135	345	8	:	:	PUNCT
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fcis-2135	345	10	-	-	SYM
fcis-2135	345	11	1358	1358	NUM
fcis-2135	345	12	.	.	PUNCT
fcis-2135	346	1	[	[	X
fcis-2135	346	2	14	14	NUM
fcis-2135	346	3	]	]	PUNCT
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fcis-2135	346	5	f	f	PROPN
fcis-2135	346	6	,	,	PUNCT
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fcis-2135	347	3	between	between	ADP
fcis-2135	347	4	traffic	traffic	NOUN
fcis-2135	347	5	participants	participant	NOUN
fcis-2135	347	6	based	base	VERB
fcis-2135	347	7	on	on	ADP
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fcis-2135	348	1	proceedings	proceeding	NOUN
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fcis-2135	348	8	.	.	PUNCT
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fcis-2135	349	2	:	:	PUNCT
fcis-2135	349	3	ieee	ieee	NOUN
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fcis-2135	349	6	:	:	PUNCT
fcis-2135	349	7	1271	1271	NUM
fcis-2135	349	8	-	-	SYM
fcis-2135	349	9	1278	1278	NUM
fcis-2135	349	10	.	.	PUNCT
fcis-2135	350	1	[	[	X
fcis-2135	350	2	15	15	NUM
fcis-2135	350	3	]	]	X
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fcis-2135	350	14	the	the	DET
fcis-2135	350	15	road	road	NOUN
fcis-2135	350	16	:	:	PUNCT
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fcis-2135	350	18	driving	drive	VERB
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fcis-2135	350	20	with	with	ADP
fcis-2135	350	21	a	a	DET
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fcis-2135	350	24	of	of	ADP
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fcis-2135	350	26	interactions[c	interactions[c	PROPN
fcis-2135	350	27	]	]	X
fcis-2135	350	28	.	.	PUNCT
fcis-2135	351	1	proceedings	proceeding	NOUN
fcis-2135	351	2	of	of	ADP
fcis-2135	351	3	the	the	DET
fcis-2135	351	4	ieee	ieee	NOUN
fcis-2135	351	5	conference	conference	NOUN
fcis-2135	351	6	on	on	ADP
fcis-2135	351	7	computer	computer	NOUN
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fcis-2135	351	9	and	and	CCONJ
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fcis-2135	351	12	.	.	PUNCT
fcis-2135	352	1	long	long	ADJ
fcis-2135	352	2	beach	beach	NOUN
fcis-2135	352	3	:	:	PUNCT
fcis-2135	352	4	ieee	ieee	PROPN
fcis-2135	352	5	cs	cs	PROPN
fcis-2135	352	6	,	,	PUNCT
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fcis-2135	352	8	:	:	PUNCT
fcis-2135	352	9	8454	8454	NUM
fcis-2135	352	10	-	-	SYM
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fcis-2135	353	1	[	[	X
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fcis-2135	353	3	]	]	X
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fcis-2135	353	5	l	l	PROPN
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fcis-2135	353	9	,	,	PUNCT
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fcis-2135	354	9	-	-	PUNCT
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fcis-2135	354	14	deployment	deployment	NOUN
fcis-2135	354	15	data[c	data[c	PROPN
fcis-2135	354	16	]	]	PUNCT
fcis-2135	354	17	.	.	PUNCT
fcis-2135	355	1	proceedings	proceeding	NOUN
fcis-2135	355	2	of	of	ADP
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fcis-2135	355	11	.	.	PUNCT
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fcis-2135	356	2	:	:	PUNCT
fcis-2135	356	3	ieee	ieee	NOUN
fcis-2135	356	4	,	,	PUNCT
fcis-2135	356	5	2018	2018	NUM
fcis-2135	356	6	:	:	PUNCT
fcis-2135	356	7	5942	5942	NUM
fcis-2135	356	8	-	-	SYM
fcis-2135	356	9	5948	5948	NUM
fcis-2135	356	10	.	.	PUNCT
fcis-2135	357	1	[	[	X
fcis-2135	357	2	17	17	NUM
fcis-2135	357	3	]	]	X
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fcis-2135	357	6	,	,	PUNCT
fcis-2135	357	7	mohan	mohan	PROPN
fcis-2135	357	8	m.	m.	PROPN
fcis-2135	357	9	trivedi	trivedi	PROPN
fcis-2135	357	10	et	et	PROPN
fcis-2135	357	11	al	al	PROPN
fcis-2135	357	12	learning	learning	PROPN
fcis-2135	357	13	and	and	CCONJ
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fcis-2135	357	15	on	on	ADP
fcis-2135	357	16	-	-	PUNCT
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fcis-2135	357	18	pedestrian	pedestrian	NOUN
fcis-2135	357	19	behavior	behavior	NOUN
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fcis-2135	357	22	]	]	PUNCT
fcis-2135	357	23	.	.	PUNCT
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fcis-2135	359	5	quintero	quintero	PROPN
fcis-2135	359	6	mínguez	mínguez	PROPN
fcis-2135	359	7	,	,	PUNCT
fcis-2135	359	8	ignacio	ignacio	PROPN
fcis-2135	359	9	parra	parra	PROPN
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fcis-2135	359	11	et	et	PROPN
fcis-2135	359	12	al	al	PROPN
fcis-2135	359	13	.	.	PROPN
fcis-2135	360	1	pedestrian	pedestrian	PROPN
fcis-2135	360	2	path	path	NOUN
fcis-2135	360	3	,	,	PUNCT
fcis-2135	360	4	pose	pose	VERB
fcis-2135	360	5	,	,	PUNCT
fcis-2135	360	6	and	and	CCONJ
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fcis-2135	360	8	prediction	prediction	NOUN
fcis-2135	360	9	through	through	ADP
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fcis-2135	360	11	process	process	NOUN
fcis-2135	360	12	dynamical	dynamical	ADJ
fcis-2135	360	13	models	model	NOUN
fcis-2135	360	14	and	and	CCONJ
fcis-2135	360	15	pedestrian	pedestrian	NOUN
fcis-2135	360	16	activity	activity	NOUN
fcis-2135	360	17	recognition.tits,2018	recognition.tits,2018	NOUN
fcis-2135	361	1	[	[	X
fcis-2135	361	2	19	19	NUM
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fcis-2135	361	13	ss	ss	PROPN
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fcis-2135	361	16	:	:	PUNCT
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fcis-2135	361	25	]	]	PUNCT
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fcis-2135	362	4	ieee	ieee	NOUN
fcis-2135	362	5	winter	winter	NOUN
fcis-2135	362	6	conference	conference	NOUN
fcis-2135	362	7	on	on	ADP
fcis-2135	362	8	applications	application	NOUN
fcis-2135	362	9	of	of	ADP
fcis-2135	362	10	computer	computer	NOUN
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fcis-2135	362	12	.	.	PUNCT
fcis-2135	363	1	lake	lake	PROPN
fcis-2135	363	2	tahoe	tahoe	PROPN
fcis-2135	363	3	:	:	PUNCT
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fcis-2135	363	5	,	,	PUNCT
fcis-2135	363	6	2018	2018	NUM
fcis-2135	363	7	:	:	PUNCT
fcis-2135	363	8	1186	1186	NUM
fcis-2135	363	9	-	-	SYM
fcis-2135	363	10	1194	1194	NUM
fcis-2135	363	11	.	.	PUNCT
fcis-2135	364	1	[	[	X
fcis-2135	364	2	20	20	NUM
fcis-2135	364	3	]	]	PUNCT
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fcis-2135	364	5	a	a	X
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fcis-2135	364	9	,	,	PUNCT
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fcis-2135	364	11	v	v	NOUN
fcis-2135	364	12	,	,	PUNCT
fcis-2135	364	13	et	et	PROPN
fcis-2135	364	14	al	al	PROPN
fcis-2135	364	15	.	.	PROPN
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fcis-2135	364	17	lstm	lstm	PROPN
fcis-2135	364	18	:	:	PUNCT
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fcis-2135	364	20	trajectory	trajectory	NOUN
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fcis-2135	364	22	in	in	ADP
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fcis-2135	364	24	spaces[c	spaces[c	NOUN
fcis-2135	364	25	]	]	PUNCT
fcis-2135	364	26	.	.	PUNCT
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fcis-2135	365	7	computer	computer	NOUN
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fcis-2135	365	10	pattern	pattern	NOUN
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fcis-2135	365	12	.	.	PUNCT
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fcis-2135	366	2	vegas	vegas	PROPN
fcis-2135	366	3	:	:	PUNCT
fcis-2135	366	4	ieee	ieee	PROPN
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fcis-2135	366	8	:	:	PUNCT
fcis-2135	366	9	961	961	NUM
fcis-2135	366	10	-	-	SYM
fcis-2135	366	11	971	971	NUM
fcis-2135	366	12	.	.	PUNCT
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fcis-2135	367	2	21	21	NUM
fcis-2135	367	3	]	]	X
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fcis-2135	367	10	wang	wang	PROPN
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fcis-2135	367	12	,	,	PUNCT
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fcis-2135	367	14	al	al	PROPN
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fcis-2135	367	25	spatial	spatial	ADJ
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fcis-2135	367	28	contexts[c	contexts[c	PROPN
fcis-2135	367	29	]	]	PUNCT
fcis-2135	367	30	.	.	PUNCT
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fcis-2135	368	4	aaai	aaai	PROPN
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fcis-2135	368	6	on	on	ADP
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fcis-2135	368	8	intelligence	intelligence	NOUN
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fcis-2135	369	1	phoenix	phoenix	PROPN
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fcis-2135	370	1	aaai	aaai	PROPN
fcis-2135	370	2	,	,	PUNCT
fcis-2135	370	3	2016	2016	NUM
fcis-2135	370	4	:	:	PUNCT
fcis-2135	370	5	194	194	NUM
fcis-2135	370	6	-	-	SYM
fcis-2135	370	7	200	200	NUM
fcis-2135	370	8	.	.	PUNCT
fcis-2135	371	1	[	[	X
fcis-2135	371	2	22	22	NUM
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fcis-2135	371	9	l	l	PROPN
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fcis-2135	371	13	f	f	PROPN
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fcis-2135	371	29	prediction[c	prediction[c	PROPN
fcis-2135	371	30	]	]	PUNCT
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fcis-2135	372	4	ieee	ieee	NOUN
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fcis-2135	372	12	.	.	PUNCT
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fcis-2135	373	2	beach	beach	NOUN
fcis-2135	373	3	:	:	PUNCT
fcis-2135	373	4	ieee	ieee	PROPN
fcis-2135	373	5	cs	cs	PROPN
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fcis-2135	373	8	:	:	PUNCT
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fcis-2135	373	10	.	.	PUNCT
fcis-2135	374	1	[	[	X
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fcis-2135	375	1	a	a	DET
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fcis-2135	375	12	]	]	PUNCT
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fcis-2135	376	6	,	,	PUNCT
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fcis-2135	376	10	-	-	SYM
fcis-2135	376	11	1546	1546	NUM
fcis-2135	376	12	.	.	PUNCT
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fcis-2135	377	9	l	l	PROPN
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fcis-2135	380	3	]	]	X
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fcis-2135	380	21	]	]	PUNCT
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fcis-2135	381	1	proceedings	proceeding	NOUN
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fcis-2135	381	12	.	.	PUNCT
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fcis-2135	382	2	:	:	PUNCT
fcis-2135	382	3	ieee	ieee	PROPN
fcis-2135	382	4	cs	cs	PROPN
fcis-2135	382	5	,	,	PUNCT
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fcis-2135	382	7	:	:	PUNCT
fcis-2135	382	8	657	657	NUM
fcis-2135	382	9	-	-	SYM
fcis-2135	382	10	666	666	NUM
fcis-2135	382	11	.	.	PUNCT
fcis-2135	383	1	[	[	X
fcis-2135	383	2	26	26	NUM
fcis-2135	383	3	]	]	X
fcis-2135	383	4	schlichtkrull	schlichtkrull	PROPN
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fcis-2135	383	13	,	,	PUNCT
fcis-2135	383	14	et	et	PROPN
fcis-2135	383	15	al	al	PROPN
fcis-2135	383	16	.	.	PROPN
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fcis-2135	383	18	relational	relational	ADJ
fcis-2135	383	19	data	datum	NOUN
fcis-2135	383	20	with	with	ADP
fcis-2135	383	21	graph	graph	NOUN
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fcis-2135	384	6	2018	2018	NUM
fcis-2135	384	7	:	:	PUNCT
fcis-2135	385	1	593	593	NUM
fcis-2135	385	2	-	-	SYM
fcis-2135	385	3	607	607	NUM
fcis-2135	385	4	.	.	PUNCT
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fcis-2135	386	20	]	]	PUNCT
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fcis-2135	388	1	seoul	seoul	PROPN
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fcis-2135	388	8	:	:	SYM
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fcis-2135	388	12	.	.	PUNCT
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fcis-2135	389	27	]	]	PUNCT
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fcis-2135	391	5	ieee	ieee	PROPN
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fcis-2135	391	9	:	:	PUNCT
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fcis-2135	392	14	cross	cross	VERB
fcis-2135	392	15	?	?	PUNCT
fcis-2135	393	1	a	a	DET
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fcis-2135	393	6	]	]	PUNCT
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fcis-2135	394	2	transactions	transaction	NOUN
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fcis-2135	394	5	transportation	transportation	NOUN
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fcis-2135	394	11	):	):	PUNCT
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fcis-2135	395	26	on	on	ADP
fcis-2135	395	27	pattern	pattern	NOUN
fcis-2135	395	28	recognition	recognition	NOUN
fcis-2135	395	29	.	.	PUNCT
fcis-2135	396	1	berlin	berlin	PROPN
fcis-2135	396	2	:	:	PUNCT
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fcis-2135	396	5	,	,	PUNCT
fcis-2135	396	6	2013	2013	NUM
fcis-2135	396	7	:	:	PUNCT
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fcis-2135	396	9	-	-	SYM
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fcis-2135	396	11	.	.	PUNCT
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fcis-2135	397	3	]	]	X
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fcis-2135	397	6	,	,	PUNCT
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fcis-2135	397	17	of	of	ADP
fcis-2135	397	18	human	human	ADJ
fcis-2135	397	19	motion[c]//proceeding	motion[c]//proceeding	PROPN
fcis-2135	397	20	of	of	ADP
fcis-2135	397	21	the	the	DET
fcis-2135	397	22	conference	conference	NOUN
fcis-2135	397	23	and	and	CCONJ
fcis-2135	397	24	workshop	workshop	NOUN
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fcis-2135	397	29	systems	system	NOUN
fcis-2135	397	30	.	.	PUNCT
fcis-2135	398	1	new	new	PROPN
fcis-2135	398	2	york	york	PROPN
fcis-2135	398	3	:	:	PUNCT
fcis-2135	398	4	curran	curran	PROPN
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fcis-2135	398	6	press	press	PROPN
fcis-2135	398	7	,	,	PUNCT
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fcis-2135	398	9	:	:	PUNCT
fcis-2135	398	10	981	981	NUM
fcis-2135	398	11	-	-	SYM
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fcis-2135	398	13	.	.	PUNCT
fcis-2135	399	1	[	[	X
fcis-2135	399	2	32	32	NUM
fcis-2135	399	3	]	]	PUNCT
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fcis-2135	399	26	]	]	PUNCT
fcis-2135	399	27	.	.	PUNCT
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fcis-2135	400	2	transactions	transaction	NOUN
fcis-2135	400	3	on	on	ADP
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fcis-2135	400	8	,	,	PUNCT
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fcis-2135	400	10	):	):	PUNCT
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fcis-2135	400	12	.	.	PUNCT
fcis-2135	401	1	[	[	X
fcis-2135	401	2	33	33	NUM
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fcis-2135	401	6	f	f	PROPN
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fcis-2135	403	9	-	-	SYM
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fcis-2135	406	21	translate[j	translate[j	NOUN
fcis-2135	406	22	]	]	PUNCT
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fcis-2135	408	1	[	[	X
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fcis-2135	409	7	:	:	PUNCT
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fcis-2135	409	9	-	-	SYM
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fcis-2135	411	1	[	[	X
fcis-2135	411	2	37	37	NUM
fcis-2135	411	3	]	]	X
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fcis-2135	412	3	ieee	ieee	NOUN
fcis-2135	412	4	press	press	NOUN
fcis-2135	412	5	,	,	PUNCT
fcis-2135	412	6	2015	2015	NUM
fcis-2135	412	7	:	:	PUNCT
fcis-2135	412	8	3488	3488	NUM
fcis-2135	412	9	-	-	SYM
fcis-2135	412	10	3496	3496	NUM
fcis-2135	412	11	.	.	PUNCT
fcis-2135	413	1	[	[	X
fcis-2135	413	2	38	38	NUM
fcis-2135	413	3	]	]	PUNCT
fcis-2135	413	4	rasmussen	rasmussen	PROPN
fcis-2135	413	5	c	c	PROPN
fcis-2135	413	6	e	e	PROPN
fcis-2135	413	7	,	,	PUNCT
fcis-2135	413	8	williams	williams	PROPN
fcis-2135	413	9	c	c	PROPN
fcis-2135	413	10	k	k	PROPN
fcis-2135	413	11	i.	i.	PROPN
fcis-2135	413	12	gaussian	gaussian	PROPN
fcis-2135	413	13	processes	process	NOUN
fcis-2135	413	14	for	for	ADP
fcis-2135	413	15	machine	machine	NOUN
fcis-2135	413	16	learning[m	learning[m	PROPN
fcis-2135	413	17	]	]	PUNCT
fcis-2135	413	18	.	.	PUNCT
fcis-2135	414	1	cambridge	cambridge	PROPN
fcis-2135	414	2	:	:	PUNCT
fcis-2135	414	3	mit	mit	PROPN
fcis-2135	414	4	press	press	NOUN
fcis-2135	414	5	,	,	PUNCT
fcis-2135	414	6	2005	2005	NUM
fcis-2135	414	7	.	.	PUNCT
fcis-2135	415	1	[	[	X
fcis-2135	415	2	39	39	NUM
fcis-2135	415	3	]	]	X
fcis-2135	415	4	hochreiter	hochreiter	PROPN
fcis-2135	415	5	s	s	PROPN
fcis-2135	415	6	,	,	PUNCT
fcis-2135	415	7	schmidhuber	schmidhuber	PROPN
fcis-2135	415	8	j.	j.	PROPN
fcis-2135	415	9	long	long	PROPN
fcis-2135	415	10	short	short	ADJ
fcis-2135	415	11	-	-	PUNCT
fcis-2135	415	12	term	term	NOUN
fcis-2135	415	13	memory[j	memory[j	NOUN
fcis-2135	415	14	]	]	PUNCT
fcis-2135	415	15	.	.	PUNCT
fcis-2135	416	1	neural	neural	ADJ
fcis-2135	416	2	computation	computation	NOUN
fcis-2135	416	3	,	,	PUNCT
fcis-2135	416	4	1997	1997	NUM
fcis-2135	416	5	,	,	PUNCT
fcis-2135	416	6	9(8	9(8	NUM
fcis-2135	416	7	):	):	PUNCT
fcis-2135	416	8	1735	1735	NUM
fcis-2135	416	9	-	-	SYM
fcis-2135	416	10	1780	1780	NUM
fcis-2135	416	11	.	.	PUNCT
fcis-2135	417	1	[	[	X
fcis-2135	417	2	40	40	NUM
fcis-2135	417	3	]	]	X
fcis-2135	417	4	lee	lee	PROPN
fcis-2135	417	5	n	n	AUX
fcis-2135	417	6	,	,	PUNCT
fcis-2135	417	7	choi	choi	PROPN
fcis-2135	417	8	w	w	PROPN
fcis-2135	417	9	,	,	PUNCT
fcis-2135	417	10	vernaza	vernaza	NOUN
fcis-2135	417	11	p	p	NOUN
fcis-2135	417	12	,	,	PUNCT
fcis-2135	417	13	et	et	PROPN
fcis-2135	417	14	al	al	PROPN
fcis-2135	417	15	.	.	PROPN
fcis-2135	417	16	desire	desire	NOUN
fcis-2135	417	17	:	:	PUNCT
fcis-2135	417	18	distant	distant	ADJ
fcis-2135	417	19	future	future	ADJ
fcis-2135	417	20	prediction	prediction	NOUN
fcis-2135	417	21	in	in	ADP
fcis-2135	417	22	dynamic	dynamic	ADJ
fcis-2135	417	23	scenes	scene	NOUN
fcis-2135	417	24	with	with	ADP
fcis-2135	417	25	interacting	interact	VERB
fcis-2135	417	26	agents[c	agents[c	PROPN
fcis-2135	417	27	]	]	PUNCT
fcis-2135	417	28	.	.	PUNCT
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fcis-2135	418	3	the	the	DET
fcis-2135	418	4	ieee	ieee	NOUN
fcis-2135	418	5	conference	conference	NOUN
fcis-2135	418	6	on	on	ADP
fcis-2135	418	7	computer	computer	NOUN
fcis-2135	418	8	vision	vision	NOUN
fcis-2135	418	9	and	and	CCONJ
fcis-2135	418	10	pattern	pattern	NOUN
fcis-2135	418	11	recognition	recognition	NOUN
fcis-2135	418	12	.	.	PUNCT
fcis-2135	419	1	honolulu	honolulu	PROPN
fcis-2135	419	2	:	:	PUNCT
fcis-2135	419	3	ieee	ieee	NOUN
fcis-2135	419	4	,	,	PUNCT
fcis-2135	419	5	2017	2017	NUM
fcis-2135	419	6	:	:	PUNCT
fcis-2135	419	7	2165	2165	NUM
fcis-2135	419	8	-	-	SYM
fcis-2135	419	9	2174	2174	NUM
fcis-2135	419	10	.	.	PUNCT
fcis-2135	420	1	[	[	X
fcis-2135	420	2	41	41	NUM
fcis-2135	420	3	]	]	PUNCT
fcis-2135	420	4	vemula	vemula	NOUN
fcis-2135	420	5	a	a	PRON
fcis-2135	420	6	,	,	PUNCT
fcis-2135	420	7	muelling	muelle	VERB
fcis-2135	420	8	k	k	NOUN
fcis-2135	420	9	,	,	PUNCT
fcis-2135	420	10	oh	oh	INTJ
fcis-2135	420	11	j.	j.	PROPN
fcis-2135	420	12	social	social	ADJ
fcis-2135	420	13	attention	attention	NOUN
fcis-2135	420	14	:	:	PUNCT
fcis-2135	420	15	modeling	model	VERB
fcis-2135	420	16	attention	attention	NOUN
fcis-2135	420	17	in	in	ADP
fcis-2135	420	18	human	human	PROPN
fcis-2135	420	19	crowds[c	crowds[c	PROPN
fcis-2135	420	20	]	]	PUNCT
fcis-2135	420	21	.	.	PUNCT
fcis-2135	421	1	proceedings	proceeding	NOUN
fcis-2135	421	2	of	of	ADP
fcis-2135	421	3	the	the	DET
fcis-2135	421	4	ieee	ieee	NOUN
fcis-2135	421	5	international	international	PROPN
fcis-2135	421	6	conference	conference	NOUN
fcis-2135	421	7	on	on	ADP
fcis-2135	421	8	robotics	robotic	NOUN
fcis-2135	421	9	and	and	CCONJ
fcis-2135	421	10	automation	automation	NOUN
fcis-2135	421	11	.	.	PUNCT
fcis-2135	422	1	brisbane	brisbane	NOUN
fcis-2135	422	2	:	:	PUNCT
fcis-2135	422	3	ieee	ieee	NOUN
fcis-2135	422	4	,	,	PUNCT
fcis-2135	422	5	2018	2018	NUM
fcis-2135	422	6	:	:	PUNCT
fcis-2135	422	7	4601	4601	NUM
fcis-2135	422	8	-	-	SYM
fcis-2135	422	9	4607	4607	NUM
fcis-2135	422	10	.	.	PUNCT
fcis-2135	423	1	[	[	X
fcis-2135	423	2	42	42	NUM
fcis-2135	423	3	]	]	X
fcis-2135	423	4	hasan	hasan	PROPN
fcis-2135	423	5	i	i	PROPN
fcis-2135	423	6	,	,	PUNCT
fcis-2135	423	7	setti	setti	PROPN
fcis-2135	423	8	f	f	PROPN
fcis-2135	423	9	,	,	PUNCT
fcis-2135	423	10	tsesmelis	tsesmelis	PROPN
fcis-2135	423	11	t	t	PROPN
fcis-2135	423	12	,	,	PUNCT
fcis-2135	423	13	et	et	PROPN
fcis-2135	423	14	al	al	PROPN
fcis-2135	423	15	.	.	PROPN
fcis-2135	423	16	mx	mx	PROPN
fcis-2135	423	17	-	-	NOUN
fcis-2135	423	18	lstm	lstm	NOUN
fcis-2135	423	19	:	:	PUNCT
fcis-2135	423	20	mixing	mix	VERB
fcis-2135	423	21	tracklets	tracklet	NOUN
fcis-2135	423	22	and	and	CCONJ
fcis-2135	423	23	vislets	vislet	NOUN
fcis-2135	423	24	to	to	PART
fcis-2135	423	25	jointly	jointly	ADV
fcis-2135	423	26	forecast	forecast	VERB
fcis-2135	423	27	trajectories	trajectory	NOUN
fcis-2135	423	28	and	and	CCONJ
fcis-2135	423	29	head	head	NOUN
fcis-2135	423	30	poses[c	poses[c	NOUN
fcis-2135	423	31	]	]	PUNCT
fcis-2135	423	32	.	.	PUNCT
fcis-2135	424	1	proceedings	proceeding	NOUN
fcis-2135	424	2	of	of	ADP
fcis-2135	424	3	the	the	DET
fcis-2135	424	4	ieee	ieee	NOUN
fcis-2135	424	5	conference	conference	NOUN
fcis-2135	424	6	on	on	ADP
fcis-2135	424	7	computer	computer	NOUN
fcis-2135	424	8	vision	vision	NOUN
fcis-2135	424	9	and	and	CCONJ
fcis-2135	424	10	pattern	pattern	NOUN
fcis-2135	424	11	recognition	recognition	NOUN
fcis-2135	424	12	.	.	PUNCT
fcis-2135	425	1	salt	salt	PROPN
fcis-2135	425	2	lake	lake	PROPN
fcis-2135	425	3	city	city	PROPN
fcis-2135	425	4	:	:	PUNCT
fcis-2135	425	5	ieee	ieee	PROPN
fcis-2135	425	6	cs	cs	PROPN
fcis-2135	425	7	,	,	PUNCT
fcis-2135	425	8	2018	2018	NUM
fcis-2135	425	9	:	:	PUNCT
fcis-2135	425	10	6067	6067	NUM
fcis-2135	425	11	-	-	SYM
fcis-2135	425	12	6076	6076	NUM
fcis-2135	425	13	.	.	PUNCT
fcis-2135	426	1	[	[	X
fcis-2135	426	2	43	43	NUM
fcis-2135	426	3	]	]	X
fcis-2135	426	4	lisotto	lisotto	PROPN
fcis-2135	426	5	m	m	PROPN
fcis-2135	426	6	,	,	PUNCT
fcis-2135	426	7	coscia	coscia	PROPN
fcis-2135	426	8	p	p	PROPN
fcis-2135	426	9	,	,	PUNCT
fcis-2135	426	10	ballan	ballan	PROPN
fcis-2135	426	11	l.	l.	PROPN
fcis-2135	426	12	social	social	PROPN
fcis-2135	426	13	and	and	CCONJ
fcis-2135	426	14	scene	scene	NOUN
fcis-2135	426	15	-	-	PUNCT
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fcis-2135	426	17	trajectory	trajectory	NOUN
fcis-2135	426	18	prediction	prediction	NOUN
fcis-2135	426	19	in	in	ADP
fcis-2135	426	20	crowded	crowded	ADJ
fcis-2135	426	21	spaces[c	spaces[c	NOUN
fcis-2135	426	22	]	]	PUNCT
fcis-2135	426	23	.	.	PUNCT
fcis-2135	427	1	proceedings	proceeding	NOUN
fcis-2135	427	2	of	of	ADP
fcis-2135	427	3	the	the	DET
fcis-2135	427	4	ieee	ieee	NOUN
fcis-2135	427	5	international	international	PROPN
fcis-2135	427	6	conference	conference	NOUN
fcis-2135	427	7	on	on	ADP
fcis-2135	427	8	computer	computer	NOUN
fcis-2135	427	9	vision	vision	NOUN
fcis-2135	427	10	workshop	workshop	NOUN
fcis-2135	427	11	.	.	PUNCT
fcis-2135	428	1	seoul	seoul	PROPN
fcis-2135	428	2	:	:	PUNCT
fcis-2135	428	3	ieee	ieee	NOUN
fcis-2135	428	4	,	,	PUNCT
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fcis-2135	428	6	:	:	PUNCT
fcis-2135	428	7	2567	2567	NUM
fcis-2135	428	8	-	-	SYM
fcis-2135	428	9	2574	2574	NUM
fcis-2135	428	10	.	.	PUNCT
fcis-2135	429	1	[	[	X
fcis-2135	429	2	44	44	NUM
fcis-2135	429	3	]	]	SYM
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fcis-2135	429	5	d	d	PROPN
fcis-2135	429	6	,	,	PUNCT
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fcis-2135	429	8	g.	g.	PROPN
fcis-2135	429	9	human	human	PROPN
fcis-2135	429	10	trajectory	trajectory	NOUN
fcis-2135	429	11	prediction	prediction	NOUN
fcis-2135	429	12	using	use	VERB
fcis-2135	429	13	spatially	spatially	ADV
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fcis-2135	429	15	deep	deep	ADJ
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fcis-2135	429	17	models[j	models[j	PROPN
fcis-2135	429	18	]	]	PUNCT
fcis-2135	429	19	.	.	PUNCT
fcis-2135	430	1	arxiv	arxiv	PROPN
fcis-2135	430	2	preprint	preprint	VERB
fcis-2135	430	3	arxiv:1705.09436	arxiv:1705.09436	PROPN
fcis-2135	430	4	,	,	PUNCT
fcis-2135	430	5	2017	2017	NUM
fcis-2135	430	6	.	.	PUNCT
fcis-2135	431	1	[	[	X
fcis-2135	431	2	45	45	NUM
fcis-2135	431	3	]	]	PUNCT
fcis-2135	431	4	fernando	fernando	PROPN
fcis-2135	431	5	t	t	PROPN
fcis-2135	431	6	,	,	PUNCT
fcis-2135	431	7	denman	denman	PROPN
fcis-2135	431	8	s	s	PROPN
fcis-2135	431	9	,	,	PUNCT
fcis-2135	431	10	sridharan	sridharan	PROPN
fcis-2135	431	11	s	s	PROPN
fcis-2135	431	12	,	,	PUNCT
fcis-2135	431	13	et	et	PROPN
fcis-2135	431	14	al	al	PROPN
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fcis-2135	432	2	attention	attention	NOUN
fcis-2135	432	3	:	:	PUNCT
fcis-2135	432	4	an	an	DET
fcis-2135	432	5	lstm	lstm	ADJ
fcis-2135	432	6	framework	framework	NOUN
fcis-2135	432	7	for	for	ADP
fcis-2135	432	8	human	human	ADJ
fcis-2135	432	9	trajectory	trajectory	NOUN
fcis-2135	432	10	prediction	prediction	NOUN
fcis-2135	432	11	and	and	CCONJ
fcis-2135	432	12	abnormal	abnormal	ADJ
fcis-2135	432	13	event	event	NOUN
fcis-2135	432	14	detection[j	detection[j	PROPN
fcis-2135	432	15	]	]	PUNCT
fcis-2135	432	16	.	.	PUNCT
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fcis-2135	433	2	networks	network	NOUN
fcis-2135	433	3	,	,	PUNCT
fcis-2135	433	4	2018	2018	NUM
fcis-2135	433	5	,	,	PUNCT
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fcis-2135	433	7	:	:	SYM
fcis-2135	433	8	466	466	NUM
fcis-2135	433	9	-	-	SYM
fcis-2135	433	10	478	478	NUM
fcis-2135	433	11	.	.	PUNCT
fcis-2135	434	1	[	[	X
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fcis-2135	434	14	neural	neural	ADJ
fcis-2135	434	15	system	system	NOUN
fcis-2135	434	16	for	for	ADP
fcis-2135	434	17	probabilistic	probabilistic	ADJ
fcis-2135	434	18	trajectory	trajectory	NOUN
fcis-2135	434	19	prediction[c]//2019	prediction[c]//2019	PROPN
fcis-2135	434	20	ieee	ieee	PROPN
fcis-2135	434	21	/	/	SYM
fcis-2135	434	22	rsj	rsj	NOUN
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fcis-2135	434	24	conference	conference	NOUN
fcis-2135	434	25	on	on	ADP
fcis-2135	434	26	intelligent	intelligent	ADJ
fcis-2135	434	27	robots	robot	NOUN
fcis-2135	434	28	and	and	CCONJ
fcis-2135	434	29	systems	system	NOUN
fcis-2135	434	30	(	(	PUNCT
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fcis-2135	434	32	)	)	PUNCT
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fcis-2135	435	2	,	,	PUNCT
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fcis-2135	435	4	:	:	PUNCT
fcis-2135	435	5	6150	6150	NUM
fcis-2135	435	6	-	-	SYM
fcis-2135	435	7	6156	6156	NUM
fcis-2135	435	8	.	.	PUNCT
fcis-2135	436	1	[	[	X
fcis-2135	436	2	47	47	NUM
fcis-2135	436	3	]	]	X
fcis-2135	436	4	xue	xue	PROPN
fcis-2135	436	5	h	h	PROPN
fcis-2135	436	6	,	,	PUNCT
fcis-2135	436	7	huynh	huynh	PROPN
fcis-2135	436	8	d	d	PROPN
fcis-2135	436	9	q	q	PROPN
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fcis-2135	436	13	a	a	DET
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fcis-2135	436	15	-	-	PUNCT
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fcis-2135	436	18	lstm	lstm	NOUN
fcis-2135	436	19	model	model	NOUN
fcis-2135	436	20	for	for	ADP
fcis-2135	436	21	pedestrian	pedestrian	NOUN
fcis-2135	436	22	trajectory	trajectory	NOUN
fcis-2135	436	23	prediction[j	prediction[j	PROPN
fcis-2135	436	24	]	]	PUNCT
fcis-2135	436	25	.	.	PUNCT
fcis-2135	437	1	ieee	ieee	NOUN
fcis-2135	437	2	access	access	NOUN
fcis-2135	437	3	,	,	PUNCT
fcis-2135	437	4	2020	2020	NUM
fcis-2135	437	5	,	,	PUNCT
fcis-2135	437	6	8	8	NUM
fcis-2135	437	7	:	:	SYM
fcis-2135	437	8	44576	44576	NUM
fcis-2135	437	9	-	-	SYM
fcis-2135	437	10	44589	44589	NUM
fcis-2135	437	11	.	.	PUNCT
fcis-2135	438	1	[	[	X
fcis-2135	438	2	48	48	NUM
fcis-2135	438	3	]	]	SYM
fcis-2135	438	4	su	su	PROPN
fcis-2135	438	5	h	h	PROPN
fcis-2135	438	6	,	,	PUNCT
fcis-2135	438	7	zhu	zhu	PROPN
fcis-2135	438	8	j	j	PROPN
fcis-2135	438	9	,	,	PUNCT
fcis-2135	438	10	dong	dong	PROPN
fcis-2135	438	11	y	y	PROPN
fcis-2135	438	12	p.	p.	PROPN
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fcis-2135	438	14	the	the	DET
fcis-2135	438	15	plausible	plausible	ADJ
fcis-2135	438	16	paths	path	NOUN
fcis-2135	438	17	in	in	ADP
fcis-2135	438	18	crowd	crowd	NOUN
fcis-2135	438	19	scenes[c	scenes[c	PROPN
fcis-2135	438	20	]	]	PUNCT
fcis-2135	438	21	.	.	PUNCT
fcis-2135	439	1	proceedings	proceeding	NOUN
fcis-2135	439	2	of	of	ADP
fcis-2135	439	3	the	the	DET
fcis-2135	439	4	international	international	ADJ
fcis-2135	439	5	joint	joint	ADJ
fcis-2135	439	6	conference	conference	NOUN
fcis-2135	439	7	on	on	ADP
fcis-2135	439	8	artificial	artificial	ADJ
fcis-2135	439	9	intelligence	intelligence	NOUN
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fcis-2135	442	9	):	):	PUNCT
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fcis-2135	444	9	):	):	PUNCT
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fcis-2135	446	2	-	-	PUNCT
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fcis-2135	459	2	:	:	PUNCT
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fcis-2135	462	8	:	:	PUNCT
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fcis-2135	471	4	aaai	aaai	PROPN
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fcis-2135	471	6	on	on	ADP
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fcis-2135	471	9	.	.	PUNCT
fcis-2135	472	1	new	new	PROPN
fcis-2135	472	2	orleans	orleans	PROPN
fcis-2135	472	3	:	:	PUNCT
fcis-2135	472	4	aaai	aaai	PROPN
fcis-2135	472	5	,	,	PUNCT
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fcis-2135	473	3	]	]	PUNCT
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fcis-2135	473	5	h	h	PROPN
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fcis-2135	473	7	tang	tang	X
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fcis-2135	473	9	,	,	PUNCT
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fcis-2135	473	11	h	h	PROPN
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fcis-2135	473	13	et	et	PROPN
fcis-2135	473	14	al	al	PROPN
fcis-2135	473	15	.	.	PROPN
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fcis-2135	473	17	spatial	spatial	ADJ
fcis-2135	473	18	-	-	PUNCT
fcis-2135	473	19	temporal	temporal	ADJ
fcis-2135	473	20	dynamics	dynamic	NOUN
fcis-2135	473	21	for	for	ADP
fcis-2135	473	22	traffic	traffic	NOUN
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fcis-2135	473	24	.	.	PUNCT
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fcis-2135	476	1	[	[	X
fcis-2135	476	2	60	60	NUM
fcis-2135	476	3	]	]	X
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fcis-2135	476	9	h	h	PROPN
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fcis-2135	476	13	z	z	PROPN
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fcis-2135	476	28	]	]	PUNCT
fcis-2135	476	29	.	.	PUNCT
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fcis-2135	477	4	ieee	ieee	NOUN
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fcis-2135	477	10	.	.	PUNCT
fcis-2135	478	1	seoul	seoul	PROPN
fcis-2135	478	2	:	:	PUNCT
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fcis-2135	478	5	ieee	ieee	NOUN
fcis-2135	478	6	,	,	PUNCT
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fcis-2135	478	8	:	:	PUNCT
fcis-2135	478	9	6271	6271	NUM
fcis-2135	478	10	-	-	SYM
fcis-2135	478	11	6280	6280	NUM
fcis-2135	478	12	.	.	PUNCT
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fcis-2135	479	11	k	k	PROPN
fcis-2135	479	12	,	,	PUNCT
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fcis-2135	479	14	al	al	PROPN
fcis-2135	479	15	.	.	PROPN
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fcis-2135	479	17	modeling	modeling	NOUN
fcis-2135	479	18	of	of	ADP
fcis-2135	479	19	multimodal	multimodal	ADJ
fcis-2135	479	20	multi	multi	ADJ
fcis-2135	479	21	-	-	ADJ
fcis-2135	479	22	human	human	ADJ
fcis-2135	479	23	behavior[c].proceedings	behavior[c].proceeding	NOUN
fcis-2135	479	24	of	of	ADP
fcis-2135	479	25	the	the	DET
fcis-2135	479	26	ieee	ieee	PROPN
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fcis-2135	479	30	robots	robot	NOUN
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fcis-2135	479	33	.	.	PUNCT
fcis-2135	480	1	madrid	madrid	PROPN
fcis-2135	480	2	:	:	PUNCT
fcis-2135	480	3	ieee	ieee	NOUN
fcis-2135	480	4	,	,	PUNCT
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fcis-2135	480	6	-	-	SYM
fcis-2135	480	7	3095	3095	NUM
fcis-2135	480	8	.	.	PUNCT
fcis-2135	481	1	[	[	X
fcis-2135	481	2	62	62	NUM
fcis-2135	481	3	]	]	PUNCT
fcis-2135	481	4	mohamed	mohame	VERB
fcis-2135	481	5	a	a	PROPN
fcis-2135	481	6	,	,	PUNCT
fcis-2135	481	7	qian	qian	PROPN
fcis-2135	481	8	k	k	PROPN
fcis-2135	481	9	,	,	PUNCT
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fcis-2135	482	2	-	-	PUNCT
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fcis-2135	482	4	:	:	PUNCT
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fcis-2135	482	7	spatio	spatio	NOUN
fcis-2135	482	8	-	-	PUNCT
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fcis-2135	482	18	]	]	PUNCT
fcis-2135	482	19	.	.	PUNCT
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fcis-2135	483	2	of	of	ADP
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fcis-2135	483	4	ieee	ieee	NOUN
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fcis-2135	483	12	.	.	PUNCT
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fcis-2135	484	2	:	:	PUNCT
fcis-2135	484	3	ieee	ieee	PROPN
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fcis-2135	484	9	-	-	SYM
fcis-2135	484	10	14420	14420	NUM
fcis-2135	484	11	.	.	PUNCT
fcis-2135	485	1	[	[	X
fcis-2135	485	2	63	63	NUM
fcis-2135	485	3	]	]	PUNCT
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fcis-2135	485	6	,	,	PUNCT
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fcis-2135	485	9	,	,	PUNCT
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fcis-2135	485	13	:	:	PUNCT
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fcis-2135	485	19	for	for	ADP
fcis-2135	485	20	human	human	ADJ
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fcis-2135	485	22	prediction[c]//proceedings	prediction[c]//proceeding	NOUN
fcis-2135	485	23	of	of	ADP
fcis-2135	485	24	the	the	DET
fcis-2135	485	25	ieee	ieee	NOUN
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fcis-2135	485	28	winter	winter	NOUN
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fcis-2135	485	30	on	on	ADP
fcis-2135	485	31	applications	application	NOUN
fcis-2135	485	32	of	of	ADP
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fcis-2135	485	35	.	.	PUNCT
fcis-2135	486	1	2021	2021	NUM
fcis-2135	486	2	:	:	PUNCT
fcis-2135	486	3	3450	3450	NUM
fcis-2135	486	4	-	-	SYM
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fcis-2135	486	6	.	.	PUNCT
fcis-2135	487	1	[	[	X
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fcis-2135	487	3	]	]	PUNCT
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fcis-2135	488	9	-	-	PUNCT
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fcis-2135	488	12	model[j	model[j	PROPN
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fcis-2135	489	6	.	.	PUNCT
fcis-2135	490	1	[	[	X
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fcis-2135	490	28	]	]	PUNCT
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fcis-2135	492	6	:	:	PUNCT
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fcis-2135	494	19	.	.	PUNCT
fcis-2135	495	1	berlin	berlin	PROPN
fcis-2135	495	2	:	:	PUNCT
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fcis-2135	495	4	press	press	NOUN
fcis-2135	495	5	,	,	PUNCT
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fcis-2135	495	7	:	:	PUNCT
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fcis-2135	495	9	-	-	SYM
fcis-2135	495	10	565	565	NUM
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fcis-2135	496	1	[	[	X
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fcis-2135	497	1	it	it	PRON
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fcis-2135	497	6	but	but	CCONJ
fcis-2135	497	7	the	the	DET
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fcis-2135	497	12	trajectory	trajectory	NOUN
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fcis-2135	497	18	.	.	PUNCT
fcis-2135	498	1	springer	springer	NOUN
fcis-2135	498	2	,	,	PUNCT
fcis-2135	498	3	cham	cham	PROPN
fcis-2135	498	4	,	,	PUNCT
fcis-2135	498	5	2020	2020	NUM
fcis-2135	498	6	:	:	PUNCT
fcis-2135	498	7	759	759	NUM
fcis-2135	498	8	-	-	SYM
fcis-2135	498	9	776	776	NUM
fcis-2135	498	10	.	.	PUNCT
fcis-2135	499	1	[	[	X
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fcis-2135	499	3	]	]	X
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fcis-2135	499	18	forecasting	forecasting	NOUN
fcis-2135	499	19	for	for	ADP
fcis-2135	499	20	multiple	multiple	ADJ
fcis-2135	499	21	intelligent	intelligent	ADJ
fcis-2135	499	22	agents	agent	NOUN
fcis-2135	499	23	in	in	ADP
fcis-2135	499	24	dynamic	dynamic	ADJ
fcis-2135	499	25	scene[j	scene[j	NOUN
fcis-2135	499	26	]	]	PUNCT
fcis-2135	499	27	.	.	PUNCT
fcis-2135	500	1	arxiv	arxiv	PROPN
fcis-2135	500	2	preprint	preprint	NOUN
fcis-2135	500	3	arxiv:2005.13133	arxiv:2005.13133	PROPN
fcis-2135	500	4	,	,	PUNCT
fcis-2135	500	5	2020	2020	NUM
fcis-2135	500	6	.	.	PUNCT
fcis-2135	501	1	[	[	X
fcis-2135	501	2	69	69	NUM
fcis-2135	501	3	]	]	PUNCT
fcis-2135	501	4	xu	xu	PROPN
fcis-2135	501	5	y	y	PROPN
fcis-2135	501	6	y	y	PROPN
fcis-2135	501	7	,	,	PUNCT
fcis-2135	501	8	piao	piao	NOUN
fcis-2135	501	9	z	z	PROPN
fcis-2135	501	10	x	x	PROPN
fcis-2135	501	11	,	,	PUNCT
fcis-2135	501	12	gao	gao	PROPN
fcis-2135	501	13	s	s	PROPN
fcis-2135	501	14	h.	h.	PROPN
fcis-2135	501	15	encoding	encode	VERB
fcis-2135	501	16	crowd	crowd	NOUN
fcis-2135	501	17	interaction	interaction	NOUN
fcis-2135	501	18	with	with	ADP
fcis-2135	501	19	deep	deep	ADJ
fcis-2135	501	20	neural	neural	ADJ
fcis-2135	501	21	network	network	NOUN
fcis-2135	501	22	for	for	ADP
fcis-2135	501	23	pedestrian	pedestrian	NOUN
fcis-2135	501	24	trajectory	trajectory	NOUN
fcis-2135	501	25	prediction[c	prediction[c	PROPN
fcis-2135	501	26	]	]	PUNCT
fcis-2135	501	27	.	.	PUNCT
fcis-2135	502	1	proceedings	proceeding	NOUN
fcis-2135	502	2	of	of	ADP
fcis-2135	502	3	the	the	DET
fcis-2135	502	4	ieee	ieee	NOUN
fcis-2135	502	5	conference	conference	NOUN
fcis-2135	502	6	on	on	ADP
fcis-2135	502	7	computer	computer	NOUN
fcis-2135	502	8	vision	vision	NOUN
fcis-2135	502	9	and	and	CCONJ
fcis-2135	502	10	pattern	pattern	NOUN
fcis-2135	502	11	recognition	recognition	NOUN
fcis-2135	502	12	.	.	PUNCT
fcis-2135	503	1	salt	salt	PROPN
fcis-2135	503	2	lake	lake	PROPN
fcis-2135	503	3	city	city	PROPN
fcis-2135	503	4	:	:	PUNCT
fcis-2135	503	5	ieee	ieee	PROPN
fcis-2135	503	6	cs	cs	PROPN
fcis-2135	503	7	,	,	PUNCT
fcis-2135	503	8	2018	2018	NUM
fcis-2135	503	9	:	:	PUNCT
fcis-2135	503	10	52755284	52755284	NUM
fcis-2135	503	11	.	.	PUNCT