id	sid	tid	token	lemma	pos
fcis-25709	1	1	frontiers	frontier	NOUN
fcis-25709	1	2	in	in	ADP
fcis-25709	1	3	computing	computing	NOUN
fcis-25709	1	4	and	and	CCONJ
fcis-25709	1	5	intelligent	intelligent	ADJ
fcis-25709	1	6	systems	system	NOUN
fcis-25709	1	7	issn	issn	VERB
fcis-25709	1	8	:	:	PUNCT
fcis-25709	1	9	2832	2832	NUM
fcis-25709	1	10	-	-	SYM
fcis-25709	1	11	6024	6024	NUM
fcis-25709	1	12	|	|	NOUN
fcis-25709	1	13	vol	vol	NOUN
fcis-25709	1	14	.	.	PROPN
fcis-25709	2	1	9	9	NUM
fcis-25709	2	2	,	,	PUNCT
fcis-25709	2	3	no	no	INTJ
fcis-25709	2	4	.	.	NOUN
fcis-25709	2	5	3	3	NUM
fcis-25709	2	6	,	,	PUNCT
fcis-25709	2	7	2024	2024	NUM
fcis-25709	2	8	11	11	NUM
fcis-25709	2	9	3d	3d	NUM
fcis-25709	2	10	point	point	NOUN
fcis-25709	2	11	cloud	cloud	ADJ
fcis-25709	2	12	semantic	semantic	ADJ
fcis-25709	2	13	segmentation	segmentation	NOUN
fcis-25709	2	14	based	base	VERB
fcis-25709	2	15	on	on	ADP
fcis-25709	2	16	multi‐	multi‐	PROPN
fcis-25709	2	17	scale	scale	NOUN
fcis-25709	2	18	dense	dense	ADJ
fcis-25709	2	19	nested	nested	ADJ
fcis-25709	2	20	networks	network	NOUN
fcis-25709	2	21	zishuo	zishuo	VERB
fcis-25709	2	22	wang	wang	PROPN
fcis-25709	2	23	1	1	NUM
fcis-25709	2	24	,	,	PUNCT
fcis-25709	2	25	tianxiang	tianxiang	PROPN
fcis-25709	2	26	lai	lai	PROPN
fcis-25709	2	27	1	1	NUM
fcis-25709	2	28	,	,	PUNCT
fcis-25709	2	29	yufeng	yufeng	PROPN
fcis-25709	2	30	wang	wang	PROPN
fcis-25709	2	31	1	1	NUM
fcis-25709	2	32	,	,	PUNCT
fcis-25709	2	33	xingquan	xingquan	PROPN
fcis-25709	2	34	gao	gao	PROPN
fcis-25709	2	35	2	2	NUM
fcis-25709	2	36	1	1	NUM
fcis-25709	2	37	school	school	NOUN
fcis-25709	2	38	of	of	ADP
fcis-25709	2	39	information	information	NOUN
fcis-25709	2	40	and	and	CCONJ
fcis-25709	2	41	control	control	PROPN
fcis-25709	2	42	engineering	engineering	PROPN
fcis-25709	2	43	,	,	PUNCT
fcis-25709	2	44	jilin	jilin	PROPN
fcis-25709	2	45	institute	institute	PROPN
fcis-25709	2	46	of	of	ADP
fcis-25709	2	47	chemical	chemical	PROPN
fcis-25709	2	48	technology	technology	PROPN
fcis-25709	2	49	,	,	PUNCT
fcis-25709	2	50	jilin	jilin	PROPN
fcis-25709	2	51	,	,	PUNCT
fcis-25709	2	52	jilin	jilin	PROPN
fcis-25709	2	53	132022	132022	NUM
fcis-25709	2	54	,	,	PUNCT
fcis-25709	2	55	china	china	PROPN
fcis-25709	2	56	2	2	NUM
fcis-25709	2	57	school	school	NOUN
fcis-25709	2	58	of	of	ADP
fcis-25709	2	59	information	information	NOUN
fcis-25709	2	60	engineering	engineering	NOUN
fcis-25709	2	61	,	,	PUNCT
fcis-25709	2	62	jilin	jilin	PROPN
fcis-25709	2	63	vocational	vocational	PROPN
fcis-25709	2	64	college	college	PROPN
fcis-25709	2	65	of	of	ADP
fcis-25709	2	66	industry	industry	NOUN
fcis-25709	2	67	and	and	CCONJ
fcis-25709	2	68	technology	technology	NOUN
fcis-25709	2	69	,	,	PUNCT
fcis-25709	2	70	jilin	jilin	PROPN
fcis-25709	2	71	,	,	PUNCT
fcis-25709	2	72	jilin	jilin	PROPN
fcis-25709	2	73	132022	132022	PROPN
fcis-25709	2	74	,	,	PUNCT
fcis-25709	2	75	china	china	PROPN
fcis-25709	2	76	abstract	abstract	NOUN
fcis-25709	2	77	:	:	PUNCT
fcis-25709	2	78	aiming	aim	VERB
fcis-25709	2	79	at	at	ADP
fcis-25709	2	80	the	the	DET
fcis-25709	2	81	problem	problem	NOUN
fcis-25709	2	82	that	that	SCONJ
fcis-25709	2	83	the	the	DET
fcis-25709	2	84	relationship	relationship	NOUN
fcis-25709	2	85	between	between	ADP
fcis-25709	2	86	geometric	geometric	ADJ
fcis-25709	2	87	features	feature	NOUN
fcis-25709	2	88	and	and	CCONJ
fcis-25709	2	89	semantic	semantic	ADJ
fcis-25709	2	90	features	feature	NOUN
fcis-25709	2	91	is	be	AUX
fcis-25709	2	92	ignored	ignore	VERB
fcis-25709	2	93	in	in	ADP
fcis-25709	2	94	the	the	DET
fcis-25709	2	95	point	point	NOUN
fcis-25709	2	96	cloud	cloud	NOUN
fcis-25709	2	97	data	datum	NOUN
fcis-25709	2	98	downsampling	downsample	VERB
fcis-25709	2	99	process	process	NOUN
fcis-25709	2	100	,	,	PUNCT
fcis-25709	2	101	which	which	PRON
fcis-25709	2	102	leads	lead	VERB
fcis-25709	2	103	to	to	ADP
fcis-25709	2	104	inaccurate	inaccurate	ADJ
fcis-25709	2	105	segmentation	segmentation	NOUN
fcis-25709	2	106	of	of	ADP
fcis-25709	2	107	object	object	NOUN
fcis-25709	2	108	boundaries	boundary	NOUN
fcis-25709	2	109	and	and	CCONJ
fcis-25709	2	110	structural	structural	ADJ
fcis-25709	2	111	details	detail	NOUN
fcis-25709	2	112	,	,	PUNCT
fcis-25709	2	113	this	this	DET
fcis-25709	2	114	paper	paper	NOUN
fcis-25709	2	115	proposes	propose	VERB
fcis-25709	2	116	a	a	DET
fcis-25709	2	117	3d	3d	NUM
fcis-25709	2	118	point	point	NOUN
fcis-25709	2	119	cloud	cloud	ADJ
fcis-25709	2	120	semantic	semantic	ADJ
fcis-25709	2	121	segmentation	segmentation	NOUN
fcis-25709	2	122	network	network	NOUN
fcis-25709	2	123	based	base	VERB
fcis-25709	2	124	on	on	ADP
fcis-25709	2	125	multi	multi	ADJ
fcis-25709	2	126	-	-	ADJ
fcis-25709	2	127	scale	scale	ADJ
fcis-25709	2	128	dense	dense	ADJ
fcis-25709	2	129	nested	nested	ADJ
fcis-25709	2	130	type	type	NOUN
fcis-25709	2	131	.	.	PUNCT
fcis-25709	3	1	firstly	firstly	ADV
fcis-25709	3	2	,	,	PUNCT
fcis-25709	3	3	a	a	DET
fcis-25709	3	4	dense	dense	ADJ
fcis-25709	3	5	nested	nested	ADJ
fcis-25709	3	6	network	network	NOUN
fcis-25709	3	7	architecture	architecture	NOUN
fcis-25709	3	8	is	be	AUX
fcis-25709	3	9	constructed	construct	VERB
fcis-25709	3	10	by	by	ADP
fcis-25709	3	11	nesting	nest	VERB
fcis-25709	3	12	multiple	multiple	ADJ
fcis-25709	3	13	multi	multi	ADJ
fcis-25709	3	14	-	-	ADJ
fcis-25709	3	15	scale	scale	ADJ
fcis-25709	3	16	feature	feature	NOUN
fcis-25709	3	17	fusion	fusion	NOUN
fcis-25709	3	18	modules	module	NOUN
fcis-25709	3	19	to	to	PART
fcis-25709	3	20	fuse	fuse	VERB
fcis-25709	3	21	multi	multi	ADJ
fcis-25709	3	22	-	-	ADJ
fcis-25709	3	23	scale	scale	ADJ
fcis-25709	3	24	features	feature	NOUN
fcis-25709	3	25	of	of	ADP
fcis-25709	3	26	different	different	ADJ
fcis-25709	3	27	directions	direction	NOUN
fcis-25709	3	28	between	between	ADP
fcis-25709	3	29	encoder	encoder	NOUN
fcis-25709	3	30	-	-	PUNCT
fcis-25709	3	31	decoder	decoder	NOUN
fcis-25709	3	32	paths	path	NOUN
fcis-25709	3	33	,	,	PUNCT
fcis-25709	3	34	so	so	SCONJ
fcis-25709	3	35	as	as	SCONJ
fcis-25709	3	36	to	to	PART
fcis-25709	3	37	effectively	effectively	ADV
fcis-25709	3	38	propagate	propagate	VERB
fcis-25709	3	39	local	local	ADJ
fcis-25709	3	40	ge	ge	PROPN
fcis-25709	3	41	-	-	PUNCT
fcis-25709	3	42	ometric	ometric	ADJ
fcis-25709	3	43	context	context	NOUN
fcis-25709	3	44	information	information	NOUN
fcis-25709	3	45	and	and	CCONJ
fcis-25709	3	46	enhance	enhance	VERB
fcis-25709	3	47	the	the	DET
fcis-25709	3	48	ability	ability	NOUN
fcis-25709	3	49	of	of	ADP
fcis-25709	3	50	cross	cross	ADJ
fcis-25709	3	51	-	-	ADJ
fcis-25709	3	52	scale	scale	ADJ
fcis-25709	3	53	information	information	NOUN
fcis-25709	3	54	interaction	interaction	NOUN
fcis-25709	3	55	.	.	PUNCT
fcis-25709	4	1	secondly	secondly	ADV
fcis-25709	4	2	,	,	PUNCT
fcis-25709	4	3	a	a	DET
fcis-25709	4	4	local	local	ADJ
fcis-25709	4	5	feature	feature	NOUN
fcis-25709	4	6	aggregation	aggregation	NOUN
fcis-25709	4	7	unit	unit	NOUN
fcis-25709	4	8	is	be	AUX
fcis-25709	4	9	constructed	construct	VERB
fcis-25709	4	10	in	in	ADP
fcis-25709	4	11	the	the	DET
fcis-25709	4	12	multi	multi	ADJ
fcis-25709	4	13	-	-	ADJ
fcis-25709	4	14	scale	scale	ADJ
fcis-25709	4	15	feature	feature	NOUN
fcis-25709	4	16	fusion	fusion	NOUN
fcis-25709	4	17	module	module	NOUN
fcis-25709	4	18	,	,	PUNCT
fcis-25709	4	19	which	which	PRON
fcis-25709	4	20	strengthens	strengthen	VERB
fcis-25709	4	21	the	the	DET
fcis-25709	4	22	structural	structural	ADJ
fcis-25709	4	23	awareness	awareness	NOUN
fcis-25709	4	24	within	within	ADP
fcis-25709	4	25	the	the	DET
fcis-25709	4	26	local	local	ADJ
fcis-25709	4	27	point	point	NOUN
fcis-25709	4	28	set	set	VERB
fcis-25709	4	29	based	base	VERB
fcis-25709	4	30	on	on	ADP
fcis-25709	4	31	graph	graph	NOUN
fcis-25709	4	32	convolution	convolution	NOUN
fcis-25709	4	33	and	and	CCONJ
fcis-25709	4	34	attention	attention	NOUN
fcis-25709	4	35	mechanism	mechanism	NOUN
fcis-25709	4	36	,	,	PUNCT
fcis-25709	4	37	and	and	CCONJ
fcis-25709	4	38	promotes	promote	VERB
fcis-25709	4	39	the	the	DET
fcis-25709	4	40	complementarity	complementarity	NOUN
fcis-25709	4	41	of	of	ADP
fcis-25709	4	42	local	local	ADJ
fcis-25709	4	43	geometric	geometric	ADJ
fcis-25709	4	44	features	feature	NOUN
fcis-25709	4	45	and	and	CCONJ
fcis-25709	4	46	abstract	abstract	ADJ
fcis-25709	4	47	semantic	semantic	ADJ
fcis-25709	4	48	information	information	NOUN
fcis-25709	4	49	.	.	PUNCT
fcis-25709	5	1	then	then	ADV
fcis-25709	5	2	,	,	PUNCT
fcis-25709	5	3	the	the	DET
fcis-25709	5	4	crosslayer	crosslayer	NOUN
fcis-25709	5	5	multi	multi	ADJ
fcis-25709	5	6	-	-	ADJ
fcis-25709	5	7	loss	loss	ADJ
fcis-25709	5	8	supervision	supervision	NOUN
fcis-25709	5	9	module	module	NOUN
fcis-25709	5	10	is	be	AUX
fcis-25709	5	11	combined	combine	VERB
fcis-25709	5	12	to	to	PART
fcis-25709	5	13	further	far	ADV
fcis-25709	5	14	optimize	optimize	VERB
fcis-25709	5	15	the	the	DET
fcis-25709	5	16	multi	multi	ADJ
fcis-25709	5	17	-	-	ADJ
fcis-25709	5	18	scale	scale	ADJ
fcis-25709	5	19	feature	feature	NOUN
fcis-25709	5	20	propagation	propagation	NOUN
fcis-25709	5	21	,	,	PUNCT
fcis-25709	5	22	which	which	PRON
fcis-25709	5	23	makes	make	VERB
fcis-25709	5	24	the	the	DET
fcis-25709	5	25	network	network	NOUN
fcis-25709	5	26	training	train	VERB
fcis-25709	5	27	more	more	ADV
fcis-25709	5	28	stable	stable	ADJ
fcis-25709	5	29	and	and	CCONJ
fcis-25709	5	30	improves	improve	VERB
fcis-25709	5	31	the	the	DET
fcis-25709	5	32	point	point	NOUN
fcis-25709	5	33	cloud	cloud	ADJ
fcis-25709	5	34	segmentation	segmentation	NOUN
fcis-25709	5	35	accuracy	accuracy	NOUN
fcis-25709	5	36	.	.	PUNCT
fcis-25709	6	1	finally	finally	ADV
fcis-25709	6	2	,	,	PUNCT
fcis-25709	6	3	this	this	DET
fcis-25709	6	4	paper	paper	NOUN
fcis-25709	6	5	verified	verify	VERB
fcis-25709	6	6	the	the	DET
fcis-25709	6	7	proposed	propose	VERB
fcis-25709	6	8	network	network	NOUN
fcis-25709	6	9	on	on	ADP
fcis-25709	6	10	the	the	DET
fcis-25709	6	11	s3dis	s3dis	PROPN
fcis-25709	6	12	dataset	dataset	NOUN
fcis-25709	6	13	.	.	PUNCT
fcis-25709	7	1	the	the	DET
fcis-25709	7	2	experimental	experimental	ADJ
fcis-25709	7	3	results	result	NOUN
fcis-25709	7	4	show	show	VERB
fcis-25709	7	5	that	that	SCONJ
fcis-25709	7	6	the	the	DET
fcis-25709	7	7	proposed	propose	VERB
fcis-25709	7	8	network	network	NOUN
fcis-25709	7	9	has	have	VERB
fcis-25709	7	10	the	the	DET
fcis-25709	7	11	mean	mean	ADJ
fcis-25709	7	12	intersection	intersection	NOUN
fcis-25709	7	13	over	over	ADP
fcis-25709	7	14	union	union	NOUN
fcis-25709	7	15	of	of	ADP
fcis-25709	7	16	71.2	71.2	NUM
fcis-25709	7	17	%	%	NOUN
fcis-25709	7	18	and	and	CCONJ
fcis-25709	7	19	the	the	DET
fcis-25709	7	20	overall	overall	ADJ
fcis-25709	7	21	accuracy	accuracy	NOUN
fcis-25709	7	22	of	of	ADP
fcis-25709	7	23	88.7	88.7	NUM
fcis-25709	7	24	%	%	NOUN
fcis-25709	7	25	,	,	PUNCT
fcis-25709	7	26	which	which	PRON
fcis-25709	7	27	is	be	AUX
fcis-25709	7	28	1.2	1.2	NUM
fcis-25709	7	29	and	and	CCONJ
fcis-25709	7	30	0.7	0.7	NUM
fcis-25709	7	31	percentage	percentage	NOUN
fcis-25709	7	32	points	point	NOUN
fcis-25709	7	33	higher	high	ADJ
fcis-25709	7	34	than	than	ADP
fcis-25709	7	35	randla	randla	NOUN
fcis-25709	7	36	-	-	PUNCT
fcis-25709	7	37	net	net	NOUN
fcis-25709	7	38	,	,	PUNCT
fcis-25709	7	39	respectively	respectively	ADV
fcis-25709	7	40	,	,	PUNCT
fcis-25709	7	41	which	which	PRON
fcis-25709	7	42	proves	prove	VERB
fcis-25709	7	43	that	that	SCONJ
fcis-25709	7	44	the	the	DET
fcis-25709	7	45	proposed	propose	VERB
fcis-25709	7	46	network	network	NOUN
fcis-25709	7	47	can	can	AUX
fcis-25709	7	48	effectively	effectively	ADV
fcis-25709	7	49	improve	improve	VERB
fcis-25709	7	50	the	the	DET
fcis-25709	7	51	accuracy	accuracy	NOUN
fcis-25709	7	52	of	of	ADP
fcis-25709	7	53	3d	3d	NUM
fcis-25709	7	54	point	point	NOUN
fcis-25709	7	55	cloud	cloud	ADJ
fcis-25709	7	56	semantic	semantic	ADJ
fcis-25709	7	57	segmentation	segmentation	NOUN
fcis-25709	7	58	.	.	PUNCT
fcis-25709	8	1	keywords	keyword	NOUN
fcis-25709	8	2	:	:	PUNCT
fcis-25709	8	3	point	point	VERB
fcis-25709	8	4	cloud	cloud	ADJ
fcis-25709	8	5	semantic	semantic	ADJ
fcis-25709	8	6	segmentation	segmentation	NOUN
fcis-25709	8	7	;	;	PUNCT
fcis-25709	8	8	nested	nested	ADJ
fcis-25709	8	9	networks	network	NOUN
fcis-25709	8	10	;	;	PUNCT
fcis-25709	8	11	multi	multi	ADJ
fcis-25709	8	12	-	-	ADJ
fcis-25709	8	13	scale	scale	ADJ
fcis-25709	8	14	feature	feature	NOUN
fcis-25709	8	15	fusion	fusion	NOUN
fcis-25709	8	16	;	;	PUNCT
fcis-25709	8	17	dense	dense	ADJ
fcis-25709	8	18	connection	connection	NOUN
fcis-25709	8	19	.	.	PUNCT
fcis-25709	9	1	1	1	X
fcis-25709	9	2	.	.	X
fcis-25709	9	3	introduction	introduction	NOUN
fcis-25709	9	4	point	point	NOUN
fcis-25709	9	5	cloud	cloud	NOUN
fcis-25709	9	6	data	datum	NOUN
fcis-25709	9	7	can	can	AUX
fcis-25709	9	8	provide	provide	VERB
fcis-25709	9	9	rich	rich	ADJ
fcis-25709	9	10	geometric	geometric	ADJ
fcis-25709	9	11	shape	shape	NOUN
fcis-25709	9	12	and	and	CCONJ
fcis-25709	9	13	depth	depth	NOUN
fcis-25709	9	14	information	information	NOUN
fcis-25709	9	15	when	when	SCONJ
fcis-25709	9	16	describing	describe	VERB
fcis-25709	9	17	three	three	NUM
fcis-25709	9	18	-	-	PUNCT
fcis-25709	9	19	dimensional	dimensional	ADJ
fcis-25709	9	20	scenes	scene	NOUN
fcis-25709	9	21	,	,	PUNCT
fcis-25709	9	22	and	and	CCONJ
fcis-25709	9	23	is	be	AUX
fcis-25709	9	24	widely	widely	ADV
fcis-25709	9	25	used	use	VERB
fcis-25709	9	26	in	in	ADP
fcis-25709	9	27	artificial	artificial	ADJ
fcis-25709	9	28	intelligence	intelligence	NOUN
fcis-25709	9	29	fields	field	NOUN
fcis-25709	9	30	such	such	ADJ
fcis-25709	9	31	as	as	ADP
fcis-25709	9	32	automatic	automatic	ADJ
fcis-25709	9	33	driving	driving	NOUN
fcis-25709	9	34	,	,	PUNCT
fcis-25709	9	35	robotics	robotic	NOUN
fcis-25709	9	36	,	,	PUNCT
fcis-25709	9	37	and	and	CCONJ
fcis-25709	9	38	three	three	NUM
fcis-25709	9	39	-	-	PUNCT
fcis-25709	9	40	dimensional	dimensional	ADJ
fcis-25709	9	41	reconstruction[1	reconstruction[1	PROPN
fcis-25709	9	42	]	]	PUNCT
fcis-25709	9	43	.	.	PUNCT
fcis-25709	10	1	the	the	DET
fcis-25709	10	2	purpose	purpose	NOUN
fcis-25709	10	3	of	of	ADP
fcis-25709	10	4	point	point	NOUN
fcis-25709	10	5	cloud	cloud	ADJ
fcis-25709	10	6	semantic	semantic	ADJ
fcis-25709	10	7	segmentation	segmentation	NOUN
fcis-25709	10	8	is	be	AUX
fcis-25709	10	9	to	to	PART
fcis-25709	10	10	identify	identify	VERB
fcis-25709	10	11	the	the	DET
fcis-25709	10	12	semantic	semantic	ADJ
fcis-25709	10	13	labels	label	NOUN
fcis-25709	10	14	of	of	ADP
fcis-25709	10	15	each	each	DET
fcis-25709	10	16	point	point	NOUN
fcis-25709	10	17	in	in	ADP
fcis-25709	10	18	the	the	DET
fcis-25709	10	19	point	point	NOUN
fcis-25709	10	20	cloud	cloud	NOUN
fcis-25709	10	21	for	for	ADP
fcis-25709	10	22	semantic	semantic	ADJ
fcis-25709	10	23	understanding	understanding	NOUN
fcis-25709	10	24	and	and	CCONJ
fcis-25709	10	25	environment	environment	NOUN
fcis-25709	10	26	perception	perception	NOUN
fcis-25709	10	27	of	of	ADP
fcis-25709	10	28	scene	scene	NOUN
fcis-25709	10	29	objects	object	NOUN
fcis-25709	10	30	.	.	PUNCT
fcis-25709	11	1	with	with	ADP
fcis-25709	11	2	the	the	DET
fcis-25709	11	3	development	development	NOUN
fcis-25709	11	4	of	of	ADP
fcis-25709	11	5	3d	3d	NUM
fcis-25709	11	6	sensing	sense	VERB
fcis-25709	11	7	technology	technology	NOUN
fcis-25709	11	8	and	and	CCONJ
fcis-25709	11	9	the	the	DET
fcis-25709	11	10	generalization	generalization	NOUN
fcis-25709	11	11	of	of	ADP
fcis-25709	11	12	data	datum	NOUN
fcis-25709	11	13	annotation[2],deep	annotation[2],deep	PROPN
fcis-25709	11	14	learning	learning	NOUN
fcis-25709	11	15	methods	method	NOUN
fcis-25709	11	16	have	have	AUX
fcis-25709	11	17	achieved	achieve	VERB
fcis-25709	11	18	good	good	ADJ
fcis-25709	11	19	results	result	NOUN
fcis-25709	11	20	on	on	ADP
fcis-25709	11	21	tasks	task	NOUN
fcis-25709	11	22	such	such	ADJ
fcis-25709	11	23	as	as	ADP
fcis-25709	11	24	image	image	NOUN
fcis-25709	11	25	denoising[3	denoising[3	PROPN
fcis-25709	11	26	]	]	PUNCT
fcis-25709	11	27	,	,	PUNCT
fcis-25709	11	28	super	super	ADJ
fcis-25709	11	29	resolution	resolution	NOUN
fcis-25709	11	30	reconstruction[4	reconstruction[4	NOUN
fcis-25709	11	31	]	]	PUNCT
fcis-25709	11	32	,	,	PUNCT
fcis-25709	11	33	object	object	VERB
fcis-25709	11	34	classification[5	classification[5	NOUN
fcis-25709	11	35	]	]	PUNCT
fcis-25709	11	36	and	and	CCONJ
fcis-25709	11	37	semantic	semantic	ADJ
fcis-25709	11	38	segmentation[6	segmentation[6	NOUN
fcis-25709	11	39	]	]	PUNCT
fcis-25709	11	40	.	.	PUNCT
fcis-25709	12	1	at	at	ADP
fcis-25709	12	2	present	present	ADJ
fcis-25709	12	3	,	,	PUNCT
fcis-25709	12	4	many	many	ADJ
fcis-25709	12	5	novels	novel	NOUN
fcis-25709	12	6	or	or	CCONJ
fcis-25709	12	7	enhanced	enhance	VERB
fcis-25709	12	8	semantic	semantic	ADJ
fcis-25709	12	9	segmentation	segmentation	NOUN
fcis-25709	12	10	methods	method	NOUN
fcis-25709	12	11	have	have	AUX
fcis-25709	12	12	been	be	AUX
fcis-25709	12	13	proposed	propose	VERB
fcis-25709	12	14	.	.	PUNCT
fcis-25709	13	1	su	su	PROPN
fcis-25709	13	2	et	et	PROPN
fcis-25709	13	3	al.[7	al.[7	PROPN
fcis-25709	13	4	]	]	PUNCT
fcis-25709	13	5	proposed	propose	VERB
fcis-25709	13	6	an	an	DET
fcis-25709	13	7	image	image	NOUN
fcis-25709	13	8	-	-	PUNCT
fcis-25709	13	9	based	base	VERB
fcis-25709	13	10	multi	multi	ADJ
fcis-25709	13	11	-	-	ADJ
fcis-25709	13	12	view	view	ADJ
fcis-25709	13	13	convolutional	convolutional	ADJ
fcis-25709	13	14	neural	neural	ADJ
fcis-25709	13	15	network	network	NOUN
fcis-25709	13	16	(	(	PUNCT
fcis-25709	13	17	mvcnn	mvcnn	PROPN
fcis-25709	13	18	)	)	PUNCT
fcis-25709	13	19	,	,	PUNCT
fcis-25709	13	20	which	which	PRON
fcis-25709	13	21	used	use	VERB
fcis-25709	13	22	cnn	cnn	PROPN
fcis-25709	13	23	to	to	PART
fcis-25709	13	24	extract	extract	VERB
fcis-25709	13	25	multi	multi	ADJ
fcis-25709	13	26	-	-	ADJ
fcis-25709	13	27	view	view	ADJ
fcis-25709	13	28	two	two	NUM
fcis-25709	13	29	-	-	PUNCT
fcis-25709	13	30	dimensional	dimensional	ADJ
fcis-25709	13	31	image	image	NOUN
fcis-25709	13	32	features	feature	VERB
fcis-25709	13	33	to	to	PART
fcis-25709	13	34	improve	improve	VERB
fcis-25709	13	35	segmentation	segmentation	NOUN
fcis-25709	13	36	accuracy	accuracy	NOUN
fcis-25709	13	37	.	.	PUNCT
fcis-25709	14	1	boulch	boulch	PROPN
fcis-25709	14	2	et	et	PROPN
fcis-25709	14	3	al.[8	al.[8	PROPN
fcis-25709	14	4	]	]	PUNCT
fcis-25709	14	5	marked	mark	VERB
fcis-25709	14	6	rgb	rgb	PROPN
fcis-25709	14	7	and	and	CCONJ
fcis-25709	14	8	depth	depth	NOUN
fcis-25709	14	9	composite	composite	ADJ
fcis-25709	14	10	views	view	NOUN
fcis-25709	14	11	pixel	pixel	VERB
fcis-25709	14	12	by	by	ADP
fcis-25709	14	13	pixel	pixel	PROPN
fcis-25709	14	14	and	and	CCONJ
fcis-25709	14	15	proposed	propose	VERB
fcis-25709	14	16	snapnet	snapnet	NOUN
fcis-25709	14	17	network	network	NOUN
fcis-25709	14	18	to	to	PART
fcis-25709	14	19	improve	improve	VERB
fcis-25709	14	20	the	the	DET
fcis-25709	14	21	segmentation	segmentation	NOUN
fcis-25709	14	22	ability	ability	NOUN
fcis-25709	14	23	in	in	ADP
fcis-25709	14	24	the	the	DET
fcis-25709	14	25	face	face	NOUN
fcis-25709	14	26	of	of	ADP
fcis-25709	14	27	large	large	ADJ
fcis-25709	14	28	-	-	PUNCT
fcis-25709	14	29	scale	scale	NOUN
fcis-25709	14	30	point	point	NOUN
fcis-25709	14	31	cloud	cloud	NOUN
fcis-25709	14	32	scenes	scene	NOUN
fcis-25709	14	33	.	.	PUNCT
fcis-25709	15	1	riegler	riegler	NOUN
fcis-25709	15	2	et	et	PROPN
fcis-25709	15	3	al.[9	al.[9	PROPN
fcis-25709	15	4	]	]	PUNCT
fcis-25709	15	5	built	build	VERB
fcis-25709	15	6	the	the	DET
fcis-25709	15	7	octnet	octnet	ADJ
fcis-25709	15	8	network	network	NOUN
fcis-25709	15	9	by	by	ADP
fcis-25709	15	10	dividing	divide	VERB
fcis-25709	15	11	space	space	NOUN
fcis-25709	15	12	by	by	ADP
fcis-25709	15	13	octree	octree	PROPN
fcis-25709	15	14	layers	layer	NOUN
fcis-25709	15	15	,	,	PUNCT
fcis-25709	15	16	which	which	PRON
fcis-25709	15	17	significantly	significantly	ADV
fcis-25709	15	18	reduced	reduce	VERB
fcis-25709	15	19	the	the	DET
fcis-25709	15	20	computing	computing	NOUN
fcis-25709	15	21	and	and	CCONJ
fcis-25709	15	22	memory	memory	NOUN
fcis-25709	15	23	requirements	requirement	NOUN
fcis-25709	15	24	.	.	PUNCT
fcis-25709	16	1	qi	qi	PROPN
fcis-25709	16	2	et	et	PROPN
fcis-25709	16	3	al.[10	al.[10	PROPN
fcis-25709	16	4	]	]	PUNCT
fcis-25709	16	5	proposed	propose	VERB
fcis-25709	16	6	pointnet	pointnet	ADJ
fcis-25709	16	7	network	network	NOUN
fcis-25709	16	8	,	,	PUNCT
fcis-25709	16	9	which	which	PRON
fcis-25709	16	10	realized	realize	VERB
fcis-25709	16	11	end	end	NOUN
fcis-25709	16	12	-	-	PUNCT
fcis-25709	16	13	to	to	ADP
fcis-25709	16	14	-	-	PUNCT
fcis-25709	16	15	end	end	NOUN
fcis-25709	16	16	semantic	semantic	ADJ
fcis-25709	16	17	segmentation	segmentation	NOUN
fcis-25709	16	18	for	for	ADP
fcis-25709	16	19	the	the	DET
fcis-25709	16	20	first	first	ADJ
fcis-25709	16	21	time	time	NOUN
fcis-25709	16	22	.	.	PUNCT
fcis-25709	17	1	however	however	ADV
fcis-25709	17	2	,	,	PUNCT
fcis-25709	17	3	it	it	PRON
fcis-25709	17	4	ignores	ignore	VERB
fcis-25709	17	5	the	the	DET
fcis-25709	17	6	rich	rich	ADJ
fcis-25709	17	7	local	local	ADJ
fcis-25709	17	8	geometric	geometric	ADJ
fcis-25709	17	9	features	feature	NOUN
fcis-25709	17	10	,	,	PUNCT
fcis-25709	17	11	resulting	result	VERB
fcis-25709	17	12	in	in	ADP
fcis-25709	17	13	low	low	ADJ
fcis-25709	17	14	semantic	semantic	ADJ
fcis-25709	17	15	segmentation	segmentation	NOUN
fcis-25709	17	16	accuracy	accuracy	NOUN
fcis-25709	17	17	for	for	ADP
fcis-25709	17	18	complex	complex	ADJ
fcis-25709	17	19	scenes	scene	NOUN
fcis-25709	17	20	.	.	PUNCT
fcis-25709	18	1	in	in	ADP
fcis-25709	18	2	order	order	NOUN
fcis-25709	18	3	to	to	PART
fcis-25709	18	4	capture	capture	VERB
fcis-25709	18	5	local	local	ADJ
fcis-25709	18	6	geometric	geometric	ADJ
fcis-25709	18	7	shapes	shape	NOUN
fcis-25709	18	8	and	and	CCONJ
fcis-25709	18	9	details	detail	NOUN
fcis-25709	18	10	from	from	ADP
fcis-25709	18	11	the	the	DET
fcis-25709	18	12	point	point	NOUN
fcis-25709	18	13	cloud	cloud	NOUN
fcis-25709	18	14	and	and	CCONJ
fcis-25709	18	15	enhance	enhance	VERB
fcis-25709	18	16	context	context	NOUN
fcis-25709	18	17	dependence	dependence	NOUN
fcis-25709	18	18	,	,	PUNCT
fcis-25709	18	19	qi	qi	PROPN
fcis-25709	18	20	et	et	NOUN
fcis-25709	18	21	al.[11	al.[11	PROPN
fcis-25709	18	22	]	]	PUNCT
fcis-25709	18	23	adopted	adopt	VERB
fcis-25709	18	24	multi	multi	ADJ
fcis-25709	18	25	-	-	ADJ
fcis-25709	18	26	scale	scale	ADJ
fcis-25709	18	27	sampling	sampling	NOUN
fcis-25709	18	28	and	and	CCONJ
fcis-25709	18	29	group	group	NOUN
fcis-25709	18	30	fusion	fusion	NOUN
fcis-25709	18	31	mechanism	mechanism	NOUN
fcis-25709	18	32	to	to	PART
fcis-25709	18	33	improve	improve	VERB
fcis-25709	18	34	the	the	DET
fcis-25709	18	35	pointnet	pointnet	ADJ
fcis-25709	18	36	network	network	NOUN
fcis-25709	18	37	,	,	PUNCT
fcis-25709	18	38	and	and	CCONJ
fcis-25709	18	39	then	then	ADV
fcis-25709	18	40	proposed	propose	VERB
fcis-25709	18	41	the	the	DET
fcis-25709	18	42	pointnet++	pointnet++	PROPN
fcis-25709	18	43	network	network	NOUN
fcis-25709	18	44	,	,	PUNCT
fcis-25709	18	45	and	and	CCONJ
fcis-25709	18	46	extracted	extract	VERB
fcis-25709	18	47	finer	fine	ADJ
fcis-25709	18	48	granularity	granularity	NOUN
fcis-25709	18	49	semantic	semantic	ADJ
fcis-25709	18	50	features	feature	NOUN
fcis-25709	18	51	by	by	ADP
fcis-25709	18	52	stacking	stack	VERB
fcis-25709	18	53	multiple	multiple	ADJ
fcis-25709	18	54	feature	feature	NOUN
fcis-25709	18	55	abstraction	abstraction	NOUN
fcis-25709	18	56	layers	layer	NOUN
fcis-25709	18	57	.	.	PUNCT
fcis-25709	19	1	hu	hu	PROPN
fcis-25709	19	2	et	et	PROPN
fcis-25709	19	3	al.[12	al.[12	PROPN
fcis-25709	19	4	]	]	PUNCT
fcis-25709	19	5	proposed	propose	VERB
fcis-25709	19	6	that	that	SCONJ
fcis-25709	19	7	randla	randla	NOUN
fcis-25709	19	8	-	-	PUNCT
fcis-25709	19	9	net	net	NOUN
fcis-25709	19	10	network	network	NOUN
fcis-25709	19	11	can	can	AUX
fcis-25709	19	12	effectively	effectively	ADV
fcis-25709	19	13	capture	capture	VERB
fcis-25709	19	14	and	and	CCONJ
fcis-25709	19	15	retain	retain	VERB
fcis-25709	19	16	local	local	ADJ
fcis-25709	19	17	geometric	geometric	ADJ
fcis-25709	19	18	features	feature	NOUN
fcis-25709	19	19	in	in	ADP
fcis-25709	19	20	point	point	NOUN
fcis-25709	19	21	clouds	cloud	NOUN
fcis-25709	19	22	by	by	ADP
fcis-25709	19	23	introducing	introduce	VERB
fcis-25709	19	24	local	local	ADJ
fcis-25709	19	25	feature	feature	NOUN
fcis-25709	19	26	aggregation	aggregation	NOUN
fcis-25709	19	27	module	module	NOUN
fcis-25709	19	28	to	to	PART
fcis-25709	19	29	model	model	VERB
fcis-25709	19	30	the	the	DET
fcis-25709	19	31	spatial	spatial	ADJ
fcis-25709	19	32	relationship	relationship	NOUN
fcis-25709	19	33	between	between	ADP
fcis-25709	19	34	points	point	NOUN
fcis-25709	19	35	.	.	PUNCT
fcis-25709	20	1	li	li	PROPN
fcis-25709	20	2	et	et	PROPN
fcis-25709	20	3	al.[13	al.[13	PROPN
fcis-25709	20	4	]	]	PUNCT
fcis-25709	20	5	developed	develop	VERB
fcis-25709	20	6	the	the	DET
fcis-25709	20	7	x	x	SYM
fcis-25709	20	8	conversion	conversion	NOUN
fcis-25709	20	9	operator	operator	NOUN
fcis-25709	20	10	pointcnn	pointcnn	NOUN
fcis-25709	20	11	and	and	CCONJ
fcis-25709	20	12	used	use	VERB
fcis-25709	20	13	it	it	PRON
fcis-25709	20	14	to	to	PART
fcis-25709	20	15	learn	learn	VERB
fcis-25709	20	16	the	the	DET
fcis-25709	20	17	characteristics	characteristic	NOUN
fcis-25709	20	18	of	of	ADP
fcis-25709	20	19	the	the	DET
fcis-25709	20	20	input	input	NOUN
fcis-25709	20	21	point	point	NOUN
fcis-25709	20	22	cloud	cloud	NOUN
fcis-25709	20	23	in	in	ADP
fcis-25709	20	24	order	order	NOUN
fcis-25709	20	25	to	to	PART
fcis-25709	20	26	obtain	obtain	VERB
fcis-25709	20	27	highlevel	highlevel	ADJ
fcis-25709	20	28	semantics	semantic	NOUN
fcis-25709	20	29	.	.	PUNCT
fcis-25709	21	1	wu	wu	PROPN
fcis-25709	21	2	et	et	PROPN
fcis-25709	21	3	al.[14	al.[14	PROPN
fcis-25709	21	4	]	]	PUNCT
fcis-25709	21	5	extended	extend	VERB
fcis-25709	21	6	the	the	DET
fcis-25709	21	7	dynamic	dynamic	ADJ
fcis-25709	21	8	filter	filter	NOUN
fcis-25709	21	9	to	to	ADP
fcis-25709	21	10	a	a	DET
fcis-25709	21	11	new	new	ADJ
fcis-25709	21	12	convolution	convolution	NOUN
fcis-25709	21	13	operation	operation	NOUN
fcis-25709	21	14	called	call	VERB
fcis-25709	21	15	pointconv	pointconv	NOUN
fcis-25709	21	16	,	,	PUNCT
fcis-25709	21	17	which	which	PRON
fcis-25709	21	18	can	can	AUX
fcis-25709	21	19	be	be	AUX
fcis-25709	21	20	used	use	VERB
fcis-25709	21	21	to	to	PART
fcis-25709	21	22	compute	compute	VERB
fcis-25709	21	23	the	the	DET
fcis-25709	21	24	features	feature	NOUN
fcis-25709	21	25	of	of	ADP
fcis-25709	21	26	a	a	DET
fcis-25709	21	27	set	set	NOUN
fcis-25709	21	28	of	of	ADP
fcis-25709	21	29	points	point	NOUN
fcis-25709	21	30	in	in	ADP
fcis-25709	21	31	threedimensional	threedimensional	ADJ
fcis-25709	21	32	space	space	NOUN
fcis-25709	21	33	.	.	PUNCT
fcis-25709	22	1	in	in	ADP
fcis-25709	22	2	addition	addition	NOUN
fcis-25709	22	3	,	,	PUNCT
fcis-25709	22	4	du	du	PROPN
fcis-25709	22	5	jing	je	VERB
fcis-25709	22	6	et	et	PROPN
fcis-25709	22	7	al	al	PROPN
fcis-25709	22	8	.	.	PUNCT
fcis-25709	23	1	[	[	X
fcis-25709	23	2	15	15	NUM
fcis-25709	23	3	]	]	PUNCT
fcis-25709	23	4	proposed	propose	VERB
fcis-25709	23	5	a	a	DET
fcis-25709	23	6	point	point	NOUN
fcis-25709	23	7	cloud	cloud	NOUN
fcis-25709	23	8	segmentation	segmentation	NOUN
fcis-25709	23	9	network	network	NOUN
fcis-25709	23	10	based	base	VERB
fcis-25709	23	11	on	on	ADP
fcis-25709	23	12	multi	multi	ADJ
fcis-25709	23	13	-	-	ADJ
fcis-25709	23	14	feature	feature	ADJ
fcis-25709	23	15	fusion	fusion	NOUN
fcis-25709	23	16	and	and	CCONJ
fcis-25709	23	17	residual	residual	ADJ
fcis-25709	23	18	optimization	optimization	NOUN
fcis-25709	23	19	,	,	PUNCT
fcis-25709	23	20	and	and	CCONJ
fcis-25709	23	21	optimized	optimize	VERB
fcis-25709	23	22	the	the	DET
fcis-25709	23	23	network	network	NOUN
fcis-25709	23	24	training	training	NOUN
fcis-25709	23	25	by	by	ADP
fcis-25709	23	26	adding	add	VERB
fcis-25709	23	27	residual	residual	ADJ
fcis-25709	23	28	blocks	block	NOUN
fcis-25709	23	29	into	into	ADP
fcis-25709	23	30	the	the	DET
fcis-25709	23	31	feature	feature	NOUN
fcis-25709	23	32	aggregation	aggregation	NOUN
fcis-25709	23	33	module	module	NOUN
fcis-25709	23	34	.	.	PUNCT
fcis-25709	24	1	liu	liu	PROPN
fcis-25709	24	2	et	et	PROPN
fcis-25709	24	3	al.[16	al.[16	PROPN
fcis-25709	24	4	]	]	PUNCT
fcis-25709	24	5	used	use	VERB
fcis-25709	24	6	a	a	DET
fcis-25709	24	7	deep	deep	ADJ
fcis-25709	24	8	network	network	NOUN
fcis-25709	24	9	pospool	pospool	NOUN
fcis-25709	24	10	and	and	CCONJ
fcis-25709	24	11	a	a	DET
fcis-25709	24	12	simple	simple	ADJ
fcis-25709	24	13	local	local	ADJ
fcis-25709	24	14	aggregation	aggregation	NOUN
fcis-25709	24	15	operator	operator	NOUN
fcis-25709	24	16	to	to	PART
fcis-25709	24	17	analyze	analyze	VERB
fcis-25709	24	18	point	point	NOUN
fcis-25709	24	19	clouds	cloud	NOUN
fcis-25709	24	20	.	.	PUNCT
fcis-25709	25	1	xu	xu	INTJ
fcis-25709	25	2	et	et	PROPN
fcis-25709	25	3	al.[17	al.[17	PROPN
fcis-25709	25	4	]	]	PUNCT
fcis-25709	25	5	proposed	propose	VERB
fcis-25709	25	6	a	a	DET
fcis-25709	25	7	position	position	NOUN
fcis-25709	25	8	-	-	PUNCT
fcis-25709	25	9	adaptive	adaptive	ADJ
fcis-25709	25	10	convolution	convolution	NOUN
fcis-25709	25	11	operator	operator	NOUN
fcis-25709	25	12	paconv	paconv	NOUN
fcis-25709	25	13	with	with	ADP
fcis-25709	25	14	dynamic	dynamic	ADJ
fcis-25709	25	15	kernel	kernel	NOUN
fcis-25709	25	16	components	component	NOUN
fcis-25709	25	17	to	to	PART
fcis-25709	25	18	make	make	VERB
fcis-25709	25	19	full	full	ADJ
fcis-25709	25	20	use	use	NOUN
fcis-25709	25	21	of	of	ADP
fcis-25709	25	22	the	the	DET
fcis-25709	25	23	characteristics	characteristic	NOUN
fcis-25709	25	24	of	of	ADP
fcis-25709	25	25	neighborhood	neighborhood	NOUN
fcis-25709	25	26	point	point	NOUN
fcis-25709	25	27	clouds	cloud	NOUN
fcis-25709	25	28	.	.	PUNCT
fcis-25709	26	1	hao	hao	PROPN
fcis-25709	26	2	wen	wen	PROPN
fcis-25709	26	3	et	et	PROPN
fcis-25709	26	4	al	al	PROPN
fcis-25709	26	5	.	.	PUNCT
fcis-25709	27	1	[	[	X
fcis-25709	27	2	18	18	NUM
fcis-25709	27	3	]	]	PUNCT
fcis-25709	27	4	built	build	VERB
fcis-25709	27	5	a	a	DET
fcis-25709	27	6	multi	multi	ADJ
fcis-25709	27	7	-	-	ADJ
fcis-25709	27	8	feature	feature	ADJ
fcis-25709	27	9	fusion	fusion	NOUN
fcis-25709	27	10	dynamic	dynamic	ADJ
fcis-25709	27	11	graph	graph	NOUN
fcis-25709	27	12	convolutional	convolutional	ADJ
fcis-25709	27	13	neural	neural	ADJ
fcis-25709	27	14	network	network	NOUN
fcis-25709	27	15	by	by	ADP
fcis-25709	27	16	mapping	map	VERB
fcis-25709	27	17	low	low	ADJ
fcis-25709	27	18	-	-	PUNCT
fcis-25709	27	19	dimensional	dimensional	ADJ
fcis-25709	27	20	geometric	geometric	ADJ
fcis-25709	27	21	features	feature	NOUN
fcis-25709	27	22	to	to	ADP
fcis-25709	27	23	high	high	ADJ
fcis-25709	27	24	-	-	PUNCT
fcis-25709	27	25	dimensional	dimensional	ADJ
fcis-25709	27	26	space	space	NOUN
fcis-25709	27	27	,	,	PUNCT
fcis-25709	27	28	extracting	extract	VERB
fcis-25709	27	29	and	and	CCONJ
fcis-25709	27	30	fusing	fuse	VERB
fcis-25709	27	31	geometric	geometric	ADJ
fcis-25709	27	32	shape	shape	NOUN
fcis-25709	27	33	features	feature	NOUN
fcis-25709	27	34	and	and	CCONJ
fcis-25709	27	35	high	high	ADJ
fcis-25709	27	36	-	-	PUNCT
fcis-25709	27	37	level	level	NOUN
fcis-25709	27	38	semantic	semantic	ADJ
fcis-25709	27	39	features	feature	NOUN
fcis-25709	27	40	,	,	PUNCT
fcis-25709	27	41	and	and	CCONJ
fcis-25709	27	42	improved	improve	VERB
fcis-25709	27	43	the	the	DET
fcis-25709	27	44	ability	ability	NOUN
fcis-25709	27	45	to	to	PART
fcis-25709	27	46	capture	capture	VERB
fcis-25709	27	47	network	network	NOUN
fcis-25709	27	48	feature	feature	NOUN
fcis-25709	27	49	distribution	distribution	NOUN
fcis-25709	27	50	.	.	PUNCT
fcis-25709	28	1	to	to	PART
fcis-25709	28	2	sum	sum	VERB
fcis-25709	28	3	up	up	ADP
fcis-25709	28	4	,	,	PUNCT
fcis-25709	28	5	the	the	DET
fcis-25709	28	6	existing	exist	VERB
fcis-25709	28	7	3d	3d	NUM
fcis-25709	28	8	point	point	NOUN
fcis-25709	28	9	cloud	cloud	ADJ
fcis-25709	28	10	semantic	semantic	ADJ
fcis-25709	28	11	segmentation	segmentation	NOUN
fcis-25709	28	12	methods	method	NOUN
fcis-25709	28	13	mainly	mainly	ADV
fcis-25709	28	14	include	include	VERB
fcis-25709	28	15	multi	multi	ADJ
fcis-25709	28	16	-	-	ADJ
fcis-25709	28	17	view	view	NOUN
fcis-25709	28	18	-	-	PUNCT
fcis-25709	28	19	based	base	VERB
fcis-25709	28	20	methods	method	NOUN
fcis-25709	28	21	,	,	PUNCT
fcis-25709	28	22	voxel	voxel	PROPN
fcis-25709	28	23	-	-	PUNCT
fcis-25709	28	24	based	base	VERB
fcis-25709	28	25	methods	method	NOUN
fcis-25709	28	26	,	,	PUNCT
fcis-25709	28	27	and	and	CCONJ
fcis-25709	28	28	point	point	NOUN
fcis-25709	28	29	-	-	PUNCT
fcis-25709	28	30	based	base	VERB
fcis-25709	28	31	methods	method	NOUN
fcis-25709	28	32	.	.	PUNCT
fcis-25709	29	1	the	the	DET
fcis-25709	29	2	multi	multi	ADJ
fcis-25709	29	3	-	-	ADJ
fcis-25709	29	4	view	view	ADJ
fcis-25709	29	5	based	base	VERB
fcis-25709	29	6	method	method	NOUN
fcis-25709	29	7	and	and	CCONJ
fcis-25709	29	8	the	the	DET
fcis-25709	29	9	voxel	voxel	PROPN
fcis-25709	29	10	-	-	PUNCT
fcis-25709	29	11	based	base	VERB
fcis-25709	29	12	method	method	NOUN
fcis-25709	29	13	will	will	AUX
fcis-25709	29	14	lose	lose	VERB
fcis-25709	29	15	part	part	NOUN
fcis-25709	29	16	of	of	ADP
fcis-25709	29	17	the	the	DET
fcis-25709	29	18	feature	feature	NOUN
fcis-25709	29	19	information	information	NOUN
fcis-25709	29	20	in	in	ADP
fcis-25709	29	21	the	the	DET
fcis-25709	29	22	process	process	NOUN
fcis-25709	29	23	of	of	ADP
fcis-25709	29	24	data	datum	NOUN
fcis-25709	29	25	form	form	NOUN
fcis-25709	29	26	conversion	conversion	NOUN
fcis-25709	29	27	,	,	PUNCT
fcis-25709	29	28	which	which	PRON
fcis-25709	29	29	also	also	ADV
fcis-25709	29	30	increases	increase	VERB
fcis-25709	29	31	the	the	DET
fcis-25709	29	32	computation	computation	NOUN
fcis-25709	29	33	cost	cost	NOUN
fcis-25709	29	34	and	and	CCONJ
fcis-25709	29	35	memory	memory	NOUN
fcis-25709	29	36	overhead	overhead	NOUN
fcis-25709	29	37	.	.	PUNCT
fcis-25709	30	1	the	the	DET
fcis-25709	30	2	point	point	NOUN
fcis-25709	30	3	based	base	VERB
fcis-25709	30	4	method	method	NOUN
fcis-25709	30	5	can	can	AUX
fcis-25709	30	6	retain	retain	VERB
fcis-25709	30	7	the	the	DET
fcis-25709	30	8	spatial	spatial	ADJ
fcis-25709	30	9	characteristics	characteristic	NOUN
fcis-25709	30	10	of	of	ADP
fcis-25709	30	11	the	the	DET
fcis-25709	30	12	original	original	ADJ
fcis-25709	30	13	point	point	NOUN
fcis-25709	30	14	cloud	cloud	NOUN
fcis-25709	30	15	data	datum	NOUN
fcis-25709	30	16	,	,	PUNCT
fcis-25709	30	17	and	and	CCONJ
fcis-25709	30	18	can	can	AUX
fcis-25709	30	19	effectively	effectively	ADV
fcis-25709	30	20	solve	solve	VERB
fcis-25709	30	21	the	the	DET
fcis-25709	30	22	problem	problem	NOUN
fcis-25709	30	23	of	of	ADP
fcis-25709	30	24	irregularity	irregularity	NOUN
fcis-25709	30	25	and	and	CCONJ
fcis-25709	30	26	disorder	disorder	NOUN
fcis-25709	30	27	of	of	ADP
fcis-25709	30	28	the	the	DET
fcis-25709	30	29	point	point	NOUN
fcis-25709	30	30	cloud	cloud	NOUN
fcis-25709	30	31	,	,	PUNCT
fcis-25709	30	32	so	so	CCONJ
fcis-25709	30	33	it	it	PRON
fcis-25709	30	34	has	have	AUX
fcis-25709	30	35	become	become	VERB
fcis-25709	30	36	the	the	DET
fcis-25709	30	37	mainstream	mainstream	NOUN
fcis-25709	30	38	research	research	NOUN
fcis-25709	30	39	12	12	NUM
fcis-25709	30	40	method	method	NOUN
fcis-25709	30	41	.	.	PUNCT
fcis-25709	31	1	however	however	ADV
fcis-25709	31	2	,	,	PUNCT
fcis-25709	31	3	in	in	ADP
fcis-25709	31	4	the	the	DET
fcis-25709	31	5	process	process	NOUN
fcis-25709	31	6	of	of	ADP
fcis-25709	31	7	point	point	NOUN
fcis-25709	31	8	sampling	sampling	NOUN
fcis-25709	31	9	,	,	PUNCT
fcis-25709	31	10	the	the	DET
fcis-25709	31	11	learning	learning	NOUN
fcis-25709	31	12	of	of	ADP
fcis-25709	31	13	local	local	ADJ
fcis-25709	31	14	features	feature	NOUN
fcis-25709	31	15	is	be	AUX
fcis-25709	31	16	limited	limit	VERB
fcis-25709	31	17	to	to	ADP
fcis-25709	31	18	the	the	DET
fcis-25709	31	19	input	input	NOUN
fcis-25709	31	20	point	point	NOUN
fcis-25709	31	21	cloud	cloud	NOUN
fcis-25709	31	22	,	,	PUNCT
fcis-25709	31	23	and	and	CCONJ
fcis-25709	31	24	the	the	DET
fcis-25709	31	25	edges	edge	NOUN
fcis-25709	31	26	of	of	ADP
fcis-25709	31	27	some	some	DET
fcis-25709	31	28	sparse	sparse	ADJ
fcis-25709	31	29	point	point	NOUN
fcis-25709	31	30	clouds	cloud	NOUN
fcis-25709	31	31	are	be	AUX
fcis-25709	31	32	still	still	ADV
fcis-25709	31	33	difficult	difficult	ADJ
fcis-25709	31	34	to	to	PART
fcis-25709	31	35	be	be	AUX
fcis-25709	31	36	accurately	accurately	ADV
fcis-25709	31	37	segmented	segment	VERB
fcis-25709	31	38	.	.	PUNCT
fcis-25709	32	1	although	although	SCONJ
fcis-25709	32	2	the	the	DET
fcis-25709	32	3	random	random	ADJ
fcis-25709	32	4	sampling	sampling	NOUN
fcis-25709	32	5	method	method	NOUN
fcis-25709	32	6	can	can	AUX
fcis-25709	32	7	reduce	reduce	VERB
fcis-25709	32	8	the	the	DET
fcis-25709	32	9	amount	amount	NOUN
fcis-25709	32	10	of	of	ADP
fcis-25709	32	11	point	point	NOUN
fcis-25709	32	12	cloud	cloud	NOUN
fcis-25709	32	13	processed	process	VERB
fcis-25709	32	14	in	in	ADP
fcis-25709	32	15	the	the	DET
fcis-25709	32	16	process	process	NOUN
fcis-25709	32	17	of	of	ADP
fcis-25709	32	18	network	network	NOUN
fcis-25709	32	19	downsampling	downsampling	NOUN
fcis-25709	32	20	,	,	PUNCT
fcis-25709	32	21	it	it	PRON
fcis-25709	32	22	sacrifices	sacrifice	VERB
fcis-25709	32	23	the	the	DET
fcis-25709	32	24	accuracy	accuracy	NOUN
fcis-25709	32	25	of	of	ADP
fcis-25709	32	26	the	the	DET
fcis-25709	32	27	point	point	NOUN
fcis-25709	32	28	cloud	cloud	ADJ
fcis-25709	32	29	feature	feature	NOUN
fcis-25709	32	30	extraction	extraction	NOUN
fcis-25709	32	31	.	.	PUNCT
fcis-25709	33	1	to	to	PART
fcis-25709	33	2	solve	solve	VERB
fcis-25709	33	3	the	the	DET
fcis-25709	33	4	above	above	ADJ
fcis-25709	33	5	problems	problem	NOUN
fcis-25709	33	6	,	,	PUNCT
fcis-25709	33	7	this	this	DET
fcis-25709	33	8	paper	paper	NOUN
fcis-25709	33	9	proposes	propose	VERB
fcis-25709	33	10	a	a	DET
fcis-25709	33	11	multiscale	multiscale	ADJ
fcis-25709	33	12	dense	dense	ADJ
fcis-25709	33	13	nested	nested	ADJ
fcis-25709	33	14	network	network	NOUN
fcis-25709	33	15	architecture	architecture	NOUN
fcis-25709	33	16	,	,	PUNCT
fcis-25709	33	17	which	which	PRON
fcis-25709	33	18	can	can	AUX
fcis-25709	33	19	extract	extract	VERB
fcis-25709	33	20	rich	rich	ADJ
fcis-25709	33	21	point	point	NOUN
fcis-25709	33	22	feature	feature	NOUN
fcis-25709	33	23	information	information	NOUN
fcis-25709	33	24	at	at	ADP
fcis-25709	33	25	different	different	ADJ
fcis-25709	33	26	network	network	NOUN
fcis-25709	33	27	depths	depth	NOUN
fcis-25709	33	28	.	.	PUNCT
fcis-25709	34	1	the	the	DET
fcis-25709	34	2	multi	multi	ADJ
fcis-25709	34	3	-	-	ADJ
fcis-25709	34	4	scale	scale	ADJ
fcis-25709	34	5	feature	feature	NOUN
fcis-25709	34	6	fusion	fusion	NOUN
fcis-25709	34	7	module	module	NOUN
fcis-25709	34	8	utilizes	utilize	VERB
fcis-25709	34	9	the	the	DET
fcis-25709	34	10	ability	ability	NOUN
fcis-25709	34	11	of	of	ADP
fcis-25709	34	12	graph	graph	NOUN
fcis-25709	34	13	convolution	convolution	NOUN
fcis-25709	34	14	and	and	CCONJ
fcis-25709	34	15	attention	attention	NOUN
fcis-25709	34	16	mechanism	mechanism	NOUN
fcis-25709	34	17	to	to	PART
fcis-25709	34	18	capture	capture	VERB
fcis-25709	34	19	information	information	NOUN
fcis-25709	34	20	in	in	ADP
fcis-25709	34	21	the	the	DET
fcis-25709	34	22	local	local	ADJ
fcis-25709	34	23	feature	feature	NOUN
fcis-25709	34	24	aggregation	aggregation	NOUN
fcis-25709	34	25	unit	unit	NOUN
fcis-25709	34	26	,	,	PUNCT
fcis-25709	34	27	so	so	SCONJ
fcis-25709	34	28	that	that	SCONJ
fcis-25709	34	29	the	the	DET
fcis-25709	34	30	geometric	geometric	ADJ
fcis-25709	34	31	structure	structure	NOUN
fcis-25709	34	32	information	information	NOUN
fcis-25709	34	33	from	from	ADP
fcis-25709	34	34	different	different	ADJ
fcis-25709	34	35	directions	direction	NOUN
fcis-25709	34	36	and	and	CCONJ
fcis-25709	34	37	levels	level	NOUN
fcis-25709	34	38	can	can	AUX
fcis-25709	34	39	be	be	AUX
fcis-25709	34	40	integrated	integrate	VERB
fcis-25709	34	41	more	more	ADV
fcis-25709	34	42	comprehensively	comprehensively	ADV
fcis-25709	34	43	.	.	PUNCT
fcis-25709	35	1	in	in	ADP
fcis-25709	35	2	order	order	NOUN
fcis-25709	35	3	to	to	PART
fcis-25709	35	4	ensure	ensure	VERB
fcis-25709	35	5	the	the	DET
fcis-25709	35	6	steady	steady	ADJ
fcis-25709	35	7	-	-	PUNCT
fcis-25709	35	8	state	state	NOUN
fcis-25709	35	9	of	of	ADP
fcis-25709	35	10	the	the	DET
fcis-25709	35	11	multi	multi	ADJ
fcis-25709	35	12	-	-	ADJ
fcis-25709	35	13	scale	scale	ADJ
fcis-25709	35	14	feature	feature	NOUN
fcis-25709	35	15	fusion	fusion	NOUN
fcis-25709	35	16	process	process	NOUN
fcis-25709	35	17	,	,	PUNCT
fcis-25709	35	18	a	a	DET
fcis-25709	35	19	crosslayer	crosslayer	NOUN
fcis-25709	35	20	multi	multi	ADJ
fcis-25709	35	21	-	-	ADJ
fcis-25709	35	22	loss	loss	ADJ
fcis-25709	35	23	monitoring	monitoring	NOUN
fcis-25709	35	24	module	module	NOUN
fcis-25709	35	25	is	be	AUX
fcis-25709	35	26	proposed	propose	VERB
fcis-25709	35	27	,	,	PUNCT
fcis-25709	35	28	which	which	PRON
fcis-25709	35	29	can	can	AUX
fcis-25709	35	30	realize	realize	VERB
fcis-25709	35	31	the	the	DET
fcis-25709	35	32	efficient	efficient	ADJ
fcis-25709	35	33	training	training	NOUN
fcis-25709	35	34	control	control	NOUN
fcis-25709	35	35	of	of	ADP
fcis-25709	35	36	the	the	DET
fcis-25709	35	37	network	network	NOUN
fcis-25709	35	38	by	by	ADP
fcis-25709	35	39	adding	add	VERB
fcis-25709	35	40	sub	sub	NOUN
fcis-25709	35	41	-	-	NOUN
fcis-25709	35	42	losses	loss	NOUN
fcis-25709	35	43	and	and	CCONJ
fcis-25709	35	44	adjusting	adjust	VERB
fcis-25709	35	45	class	class	NOUN
fcis-25709	35	46	weights	weight	NOUN
fcis-25709	35	47	.	.	PUNCT
fcis-25709	36	1	2	2	X
fcis-25709	36	2	.	.	X
fcis-25709	36	3	network	network	NOUN
fcis-25709	36	4	model	model	NOUN
fcis-25709	36	5	2.1	2.1	NUM
fcis-25709	36	6	.	.	PUNCT
fcis-25709	37	1	dense	dense	ADJ
fcis-25709	37	2	nested	nested	ADJ
fcis-25709	37	3	network	network	NOUN
fcis-25709	37	4	architecture	architecture	NOUN
fcis-25709	37	5	the	the	DET
fcis-25709	37	6	network	network	NOUN
fcis-25709	37	7	proposed	propose	VERB
fcis-25709	37	8	in	in	ADP
fcis-25709	37	9	this	this	DET
fcis-25709	37	10	paper	paper	NOUN
fcis-25709	37	11	is	be	AUX
fcis-25709	37	12	based	base	VERB
fcis-25709	37	13	on	on	ADP
fcis-25709	37	14	multi	multi	ADJ
fcis-25709	37	15	-	-	ADJ
fcis-25709	37	16	scale	scale	ADJ
fcis-25709	37	17	dense	dense	ADJ
fcis-25709	37	18	nested	nested	ADJ
fcis-25709	37	19	network	network	NOUN
fcis-25709	37	20	architecture	architecture	NOUN
fcis-25709	37	21	.	.	PUNCT
fcis-25709	38	1	as	as	SCONJ
fcis-25709	38	2	shown	show	VERB
fcis-25709	38	3	in	in	ADP
fcis-25709	38	4	figure	figure	NOUN
fcis-25709	38	5	1	1	NUM
fcis-25709	38	6	,	,	PUNCT
fcis-25709	38	7	the	the	DET
fcis-25709	38	8	black	black	ADJ
fcis-25709	38	9	solid	solid	ADJ
fcis-25709	38	10	and	and	CCONJ
fcis-25709	38	11	dotted	dotted	ADJ
fcis-25709	38	12	arrows	arrow	NOUN
fcis-25709	38	13	are	be	AUX
fcis-25709	38	14	direct	direct	ADJ
fcis-25709	38	15	connection	connection	NOUN
fcis-25709	38	16	and	and	CCONJ
fcis-25709	38	17	dense	dense	ADJ
fcis-25709	38	18	jump	jump	NOUN
fcis-25709	38	19	connection	connection	NOUN
fcis-25709	38	20	respectively	respectively	ADV
fcis-25709	38	21	,	,	PUNCT
fcis-25709	38	22	the	the	DET
fcis-25709	38	23	blue	blue	ADJ
fcis-25709	38	24	and	and	CCONJ
fcis-25709	38	25	purple	purple	ADJ
fcis-25709	38	26	arrows	arrow	NOUN
fcis-25709	38	27	are	be	AUX
fcis-25709	38	28	up	up	ADV
fcis-25709	38	29	-	-	PUNCT
fcis-25709	38	30	sampling	sample	VERB
fcis-25709	38	31	and	and	CCONJ
fcis-25709	38	32	down	down	ADV
fcis-25709	38	33	-	-	PUNCT
fcis-25709	38	34	sampling	sample	VERB
fcis-25709	38	35	processes	process	NOUN
fcis-25709	38	36	respectively	respectively	ADV
fcis-25709	38	37	,	,	PUNCT
fcis-25709	38	38	and	and	CCONJ
fcis-25709	38	39	the	the	DET
fcis-25709	38	40	circle	circle	NOUN
fcis-25709	38	41	part	part	NOUN
fcis-25709	38	42	is	be	AUX
fcis-25709	38	43	the	the	DET
fcis-25709	38	44	multi	multi	ADJ
fcis-25709	38	45	-	-	ADJ
fcis-25709	38	46	scale	scale	ADJ
fcis-25709	38	47	feature	feature	NOUN
fcis-25709	38	48	fusion	fusion	NOUN
fcis-25709	38	49	module	module	NOUN
fcis-25709	38	50	(	(	PUNCT
fcis-25709	38	51	mffm	mffm	NOUN
fcis-25709	38	52	)	)	PUNCT
fcis-25709	38	53	,	,	PUNCT
fcis-25709	38	54	which	which	PRON
fcis-25709	38	55	defines	define	VERB
fcis-25709	38	56	the	the	DET
fcis-25709	38	57	output	output	NOUN
fcis-25709	38	58	feature	feature	NOUN
fcis-25709	38	59	of	of	ADP
fcis-25709	38	60	each	each	DET
fcis-25709	38	61	mffm	mffm	NOUN
fcis-25709	38	62	as	as	ADP
fcis-25709	38	63	,	,	PUNCT
fcis-25709	38	64	where	where	SCONJ
fcis-25709	38	65	and	and	CCONJ
fcis-25709	38	66	respectively	respectively	ADV
fcis-25709	38	67	represent	represent	VERB
fcis-25709	38	68	the	the	DET
fcis-25709	38	69	depth	depth	NOUN
fcis-25709	38	70	and	and	CCONJ
fcis-25709	38	71	width	width	NOUN
fcis-25709	38	72	of	of	ADP
fcis-25709	38	73	the	the	DET
fcis-25709	38	74	current	current	ADJ
fcis-25709	38	75	network	network	NOUN
fcis-25709	38	76	layer	layer	NOUN
fcis-25709	38	77	.	.	PUNCT
fcis-25709	39	1	therefore	therefore	ADV
fcis-25709	39	2	,	,	PUNCT
fcis-25709	39	3	the	the	DET
fcis-25709	39	4	output	output	NOUN
fcis-25709	39	5	characteristics	characteristic	NOUN
fcis-25709	39	6	of	of	ADP
fcis-25709	39	7	each	each	DET
fcis-25709	39	8	mffm	mffm	NOUN
fcis-25709	39	9	in	in	ADP
fcis-25709	39	10	the	the	DET
fcis-25709	39	11	second	second	ADJ
fcis-25709	39	12	layer	layer	NOUN
fcis-25709	39	13	are	be	AUX
fcis-25709	39	14	shown	show	VERB
fcis-25709	39	15	in	in	ADP
fcis-25709	39	16	formula	formula	NOUN
fcis-25709	39	17	(	(	PUNCT
fcis-25709	39	18	1	1	NUM
fcis-25709	39	19	):	):	PUNCT
fcis-25709	39	20			NOUN
fcis-25709	39	21			SYM
fcis-25709	39	22			NOUN
fcis-25709	39	23			SYM
fcis-25709	39	24			NOUN
fcis-25709	39	25			SYM
fcis-25709	39	26			NOUN
fcis-25709	39	27			SYM
fcis-25709	39	28			NOUN
fcis-25709	39	29			SYM
fcis-25709	39	30			NOUN
fcis-25709	39	31			SYM
fcis-25709	39	32			NOUN
fcis-25709	39	33			PROPN
fcis-25709	39	34	1	1	NUM
fcis-25709	39	35	,	,	PUNCT
fcis-25709	39	36	,	,	PUNCT
fcis-25709	39	37	,	,	PUNCT
fcis-25709	39	38	1	1	NUM
fcis-25709	39	39	1	1	NUM
fcis-25709	39	40	,	,	PUNCT
fcis-25709	39	41	1	1	NUM
fcis-25709	39	42	,	,	PUNCT
fcis-25709	39	43	1	1	NUM
fcis-25709	39	44	,	,	PUNCT
fcis-25709	39	45	1	1	NUM
fcis-25709	39	46	1	1	NUM
fcis-25709	39	47	,	,	PUNCT
fcis-25709	39	48	1	1	NUM
fcis-25709	39	49	,	,	PUNCT
fcis-25709	39	50	1	1	NUM
fcis-25709	39	51	,	,	PUNCT
fcis-25709	39	52	0	0	NUM
fcis-25709	39	53	0	0	NUM
fcis-25709	39	54	,	,	PUNCT
fcis-25709	39	55	,	,	PUNCT
fcis-25709	39	56	1	1	NUM
fcis-25709	39	57	,	,	PUNCT
fcis-25709	39	58	2,3	2,3	NUM
fcis-25709	39	59	,	,	PUNCT
fcis-25709	39	60	,	,	PUNCT
fcis-25709	39	61	,	,	PUNCT
fcis-25709	39	62	4	4	NUM
fcis-25709	39	63	i	i	NOUN
fcis-25709	39	64	j	j	VERB
fcis-25709	40	1	i	i	PRON
fcis-25709	40	2	j	j	VERB
fcis-25709	41	1	i	i	PRON
fcis-25709	41	2	j	j	VERB
fcis-25709	42	1	i	i	PRON
fcis-25709	42	2	j	j	VERB
fcis-25709	43	1	i	i	PRON
fcis-25709	43	2	j	j	VERB
fcis-25709	44	1	i	i	PRON
fcis-25709	44	2	j	j	VERB
fcis-25709	45	1	i	i	PRON
fcis-25709	45	2	j	j	VERB
fcis-25709	46	1	i	i	PRON
fcis-25709	46	2	j	j	VERB
fcis-25709	47	1	i	i	INTJ
fcis-25709	48	1	d	d	NOUN
fcis-25709	48	2	f	f	PROPN
fcis-25709	49	1	j	j	PROPN
fcis-25709	49	2	f	f	INTJ
fcis-25709	50	1	fa	fa	INTJ
fcis-25709	50	2	f	f	PROPN
fcis-25709	51	1	d	d	X
fcis-25709	51	2	f	f	X
fcis-25709	51	3	u	u	X
fcis-25709	51	4	f	f	PROPN
fcis-25709	51	5	j	j	PROPN
fcis-25709	52	1	fa	fa	INTJ
fcis-25709	52	2	f	f	PROPN
fcis-25709	53	1	d	d	X
fcis-25709	53	2	f	f	X
fcis-25709	53	3	u	u	X
fcis-25709	53	4	f	f	PROPN
fcis-25709	53	5	f	f	PROPN
fcis-25709	53	6	j	j	PROPN
fcis-25709	53	7			NOUN
fcis-25709	53	8			PRON
fcis-25709	54	1			PRON
fcis-25709	54	2			PROPN
fcis-25709	54	3			PROPN
fcis-25709	54	4			PROPN
fcis-25709	54	5			PUNCT
fcis-25709	54	6			PROPN
fcis-25709	54	7			PROPN
fcis-25709	54	8			PROPN
fcis-25709	54	9			VERB
fcis-25709	54	10			NOUN
fcis-25709	54	11			ADP
fcis-25709	55	1			PROPN
fcis-25709	55	2			ADJ
fcis-25709	55	3			PROPN
fcis-25709	55	4			PROPN
fcis-25709	55	5			NUM
fcis-25709	55	6			PROPN
fcis-25709	55	7			PROPN
fcis-25709	55	8			PROPN
fcis-25709	55	9			PROPN
fcis-25709	55	10			PROPN
fcis-25709	55	11			NUM
fcis-25709	55	12			PROPN
fcis-25709	55	13			PROPN
fcis-25709	55	14			X
fcis-25709	55	15			PROPN
fcis-25709	55	16	(	(	PUNCT
fcis-25709	55	17	1	1	NUM
fcis-25709	55	18	)	)	PUNCT
fcis-25709	55	19	among	among	ADP
fcis-25709	55	20			ADJ
fcis-25709	55	21	,	,	PROPN
fcis-25709	55	22	is	be	AUX
fcis-25709	55	23	the	the	DET
fcis-25709	55	24	feature	feature	NOUN
fcis-25709	55	25	splice	splice	NOUN
fcis-25709	55	26	,	,	PUNCT
fcis-25709	55	27			NOUN
fcis-25709	55	28	fa	fa	NOUN
fcis-25709	55	29	is	be	AUX
fcis-25709	55	30	the	the	DET
fcis-25709	55	31	aggregation	aggregation	NOUN
fcis-25709	55	32	of	of	ADP
fcis-25709	55	33	features	feature	NOUN
fcis-25709	55	34	in	in	ADP
fcis-25709	55	35	the	the	DET
fcis-25709	55	36	block	block	NOUN
fcis-25709	55	37	,	,	PUNCT
fcis-25709	55	38			PROPN
fcis-25709	55	39	d	d	PUNCT
fcis-25709	55	40	and	and	CCONJ
fcis-25709	55	41			PROPN
fcis-25709	55	42	u	u	PROPN
fcis-25709	55	43	are	be	AUX
fcis-25709	55	44	downsampled	downsample	VERB
fcis-25709	55	45	and	and	CCONJ
fcis-25709	55	46	upsampled	upsample	VERB
fcis-25709	55	47	respectively	respectively	ADV
fcis-25709	55	48	.	.	PUNCT
fcis-25709	56	1	0,0	0,0	NUM
fcis-25709	56	2	5,0f	5,0f	NUM
fcis-25709	56	3	f	f	PROPN
fcis-25709	56	4	indicates	indicate	VERB
fcis-25709	56	5	the	the	DET
fcis-25709	56	6	encoder	encoder	NOUN
fcis-25709	56	7	path	path	NOUN
fcis-25709	56	8	direction	direction	NOUN
fcis-25709	56	9	,	,	PUNCT
fcis-25709	56	10	5,0	5,0	NUM
fcis-25709	56	11	0,5f	0,5f	NUM
fcis-25709	57	1	f	f	NUM
fcis-25709	57	2	is	be	AUX
fcis-25709	57	3	the	the	DET
fcis-25709	57	4	decoder	decoder	NOUN
fcis-25709	57	5	path	path	NOUN
fcis-25709	57	6	direction	direction	NOUN
fcis-25709	57	7	.	.	PUNCT
fcis-25709	58	1	mffm	mffm	NOUN
fcis-25709	58	2	is	be	AUX
fcis-25709	58	3	densely	densely	ADV
fcis-25709	58	4	nested	nested	ADJ
fcis-25709	58	5	in	in	ADP
fcis-25709	58	6	coding	code	VERB
fcis-25709	58	7	-	-	PUNCT
fcis-25709	58	8	decoder	decoder	NOUN
fcis-25709	58	9	paths	path	NOUN
fcis-25709	58	10	of	of	ADP
fcis-25709	58	11	different	different	ADJ
fcis-25709	58	12	depths	depth	NOUN
fcis-25709	58	13	to	to	PART
fcis-25709	58	14	accurately	accurately	ADV
fcis-25709	58	15	extract	extract	VERB
fcis-25709	58	16	point	point	NOUN
fcis-25709	58	17	-	-	PUNCT
fcis-25709	58	18	by	by	ADP
fcis-25709	58	19	-	-	PUNCT
fcis-25709	58	20	point	point	NOUN
fcis-25709	58	21	local	local	ADJ
fcis-25709	58	22	geometric	geometric	ADJ
fcis-25709	58	23	details	detail	NOUN
fcis-25709	58	24	,	,	PUNCT
fcis-25709	58	25	thus	thus	ADV
fcis-25709	58	26	propagating	propagate	VERB
fcis-25709	58	27	multi	multi	ADJ
fcis-25709	58	28	-	-	ADJ
fcis-25709	58	29	scale	scale	ADJ
fcis-25709	58	30	features	feature	VERB
fcis-25709	58	31	more	more	ADV
fcis-25709	58	32	effectively	effectively	ADV
fcis-25709	58	33	.	.	PUNCT
fcis-25709	59	1	fig	fig	NOUN
fcis-25709	59	2	1	1	NUM
fcis-25709	59	3	.	.	PUNCT
fcis-25709	60	1	mdnn	mdnn	NOUN
fcis-25709	60	2	network	network	NOUN
fcis-25709	60	3	architecture	architecture	NOUN
fcis-25709	60	4	first	first	ADV
fcis-25709	60	5	,	,	PUNCT
fcis-25709	60	6	the	the	DET
fcis-25709	60	7	point	point	NOUN
fcis-25709	60	8	cloud	cloud	NOUN
fcis-25709	60	9	is	be	AUX
fcis-25709	60	10	input	input	VERB
fcis-25709	60	11	into	into	ADP
fcis-25709	60	12	a	a	DET
fcis-25709	60	13	shared	share	VERB
fcis-25709	60	14	fully	fully	ADV
fcis-25709	60	15	connected	connect	VERB
fcis-25709	60	16	layer	layer	NOUN
fcis-25709	60	17	,	,	PUNCT
fcis-25709	60	18	extracting	extract	VERB
fcis-25709	60	19	the	the	DET
fcis-25709	60	20	initial	initial	ADJ
fcis-25709	60	21	features	feature	NOUN
fcis-25709	60	22	of	of	ADP
fcis-25709	60	23	each	each	DET
fcis-25709	60	24	point	point	NOUN
fcis-25709	60	25	from	from	ADP
fcis-25709	60	26	the	the	DET
fcis-25709	60	27	original	original	ADJ
fcis-25709	60	28	point	point	NOUN
fcis-25709	60	29	cloud	cloud	NOUN
fcis-25709	60	30	.	.	PUNCT
fcis-25709	61	1	secondly	secondly	ADV
fcis-25709	61	2	,	,	PUNCT
fcis-25709	61	3	the	the	DET
fcis-25709	61	4	learned	learn	VERB
fcis-25709	61	5	feature	feature	NOUN
fcis-25709	61	6	information	information	NOUN
fcis-25709	61	7	is	be	AUX
fcis-25709	61	8	input	input	VERB
fcis-25709	61	9	into	into	ADP
fcis-25709	61	10	0,0f	0,0f	NOUN
fcis-25709	61	11	,	,	PUNCT
fcis-25709	61	12	through	through	ADP
fcis-25709	61	13	horizontal	horizontal	ADJ
fcis-25709	61	14	and	and	CCONJ
fcis-25709	61	15	vertical	vertical	ADJ
fcis-25709	61	16	connections	connection	NOUN
fcis-25709	61	17	,	,	PUNCT
fcis-25709	61	18	feature	feature	NOUN
fcis-25709	61	19	information	information	NOUN
fcis-25709	61	20	can	can	AUX
fcis-25709	61	21	be	be	AUX
fcis-25709	61	22	propagated	propagate	VERB
fcis-25709	61	23	between	between	ADP
fcis-25709	61	24	different	different	ADJ
fcis-25709	61	25	levels	level	NOUN
fcis-25709	61	26	.	.	PUNCT
fcis-25709	62	1	compared	compare	VERB
fcis-25709	62	2	with	with	ADP
fcis-25709	62	3	methods	method	NOUN
fcis-25709	62	4	such	such	ADJ
fcis-25709	62	5	as	as	ADP
fcis-25709	62	6	farthest	farth	ADJ
fcis-25709	62	7	point	point	NOUN
fcis-25709	62	8	sampling[19	sampling[19	ADV
fcis-25709	62	9	]	]	PUNCT
fcis-25709	62	10	,	,	PUNCT
fcis-25709	62	11	and	and	CCONJ
fcis-25709	62	12	inverse	inverse	NOUN
fcis-25709	62	13	density	density	NOUN
fcis-25709	62	14	sampling	sample	VERB
fcis-25709	62	15	[	[	X
fcis-25709	62	16	20	20	NUM
fcis-25709	62	17	]	]	PUNCT
fcis-25709	62	18	,	,	PUNCT
fcis-25709	62	19	mdnn	mdnn	NOUN
fcis-25709	62	20	uses	use	VERB
fcis-25709	62	21	random	random	ADJ
fcis-25709	62	22	sampling	sampling	NOUN
fcis-25709	62	23	operations	operation	NOUN
fcis-25709	62	24	to	to	PART
fcis-25709	62	25	reduce	reduce	VERB
fcis-25709	62	26	the	the	DET
fcis-25709	62	27	spatial	spatial	ADJ
fcis-25709	62	28	resolution	resolution	NOUN
fcis-25709	62	29	of	of	ADP
fcis-25709	62	30	point	point	NOUN
fcis-25709	62	31	features	feature	NOUN
fcis-25709	62	32	,	,	PUNCT
fcis-25709	62	33	thereby	thereby	ADV
fcis-25709	62	34	improving	improve	VERB
fcis-25709	62	35	computational	computational	ADJ
fcis-25709	62	36	efficiency	efficiency	NOUN
fcis-25709	62	37	and	and	CCONJ
fcis-25709	62	38	abstraction	abstraction	NOUN
fcis-25709	62	39	.	.	PUNCT
fcis-25709	63	1	then	then	ADV
fcis-25709	63	2	,	,	PUNCT
fcis-25709	63	3	along	along	ADP
fcis-25709	63	4	the	the	DET
fcis-25709	63	5	direction	direction	NOUN
fcis-25709	63	6	of	of	ADP
fcis-25709	63	7	the	the	DET
fcis-25709	63	8	encoder	encoder	NOUN
fcis-25709	63	9	path	path	NOUN
fcis-25709	63	10	,	,	PUNCT
fcis-25709	63	11	the	the	DET
fcis-25709	63	12	network	network	NOUN
fcis-25709	63	13	gradually	gradually	ADV
fcis-25709	63	14	sparse	sparse	VERB
fcis-25709	63	15	the	the	DET
fcis-25709	63	16	point	point	NOUN
fcis-25709	63	17	cloud	cloud	NOUN
fcis-25709	63	18	(	(	PUNCT
fcis-25709	63	19	where	where	SCONJ
fcis-25709	63	20	n	n	X
fcis-25709	63	21	is	be	AUX
fcis-25709	63	22	the	the	DET
fcis-25709	63	23	number	number	NOUN
fcis-25709	63	24	of	of	ADP
fcis-25709	63	25	points	point	NOUN
fcis-25709	63	26	)	)	PUNCT
fcis-25709	63	27	in	in	ADP
fcis-25709	63	28	the	the	DET
fcis-25709	63	29	order	order	NOUN
fcis-25709	63	30	of	of	ADP
fcis-25709	63	31	(	(	PUNCT
fcis-25709	63	32	n→n/4→n/16→n/64→n/256→n/512	n→n/4→n/16→n/64→n/256→n/512	PROPN
fcis-25709	63	33	)	)	PUNCT
fcis-25709	63	34	,	,	PUNCT
fcis-25709	63	35	each	each	DET
fcis-25709	63	36	level	level	NOUN
fcis-25709	63	37	of	of	ADP
fcis-25709	63	38	mffm	mffm	NOUN
fcis-25709	63	39	learns	learn	VERB
fcis-25709	63	40	the	the	DET
fcis-25709	63	41	multi	multi	NOUN
fcis-25709	63	42	-	-	NOUN
fcis-25709	63	43	scale	scale	NOUN
fcis-25709	63	44	of	of	ADP
fcis-25709	63	45	point	point	NOUN
fcis-25709	63	46	features	feature	NOUN
fcis-25709	63	47	at	at	ADP
fcis-25709	63	48	multiple	multiple	ADJ
fcis-25709	63	49	network	network	NOUN
fcis-25709	63	50	levels	level	NOUN
fcis-25709	63	51	,	,	PUNCT
fcis-25709	63	52	and	and	CCONJ
fcis-25709	63	53	gradually	gradually	ADV
fcis-25709	63	54	expands	expand	VERB
fcis-25709	63	55	the	the	DET
fcis-25709	63	56	receiving	receive	VERB
fcis-25709	63	57	domain	domain	NOUN
fcis-25709	63	58	to	to	PART
fcis-25709	63	59	obtain	obtain	VERB
fcis-25709	63	60	higher	high	ADJ
fcis-25709	63	61	level	level	NOUN
fcis-25709	63	62	of	of	ADP
fcis-25709	63	63	abstract	abstract	ADJ
fcis-25709	63	64	semantic	semantic	ADJ
fcis-25709	63	65	features	feature	NOUN
fcis-25709	63	66	.	.	PUNCT
fcis-25709	64	1	at	at	ADP
fcis-25709	64	2	the	the	DET
fcis-25709	64	3	same	same	ADJ
fcis-25709	64	4	time	time	NOUN
fcis-25709	64	5	,	,	PUNCT
fcis-25709	64	6	along	along	ADP
fcis-25709	64	7	the	the	DET
fcis-25709	64	8	direction	direction	NOUN
fcis-25709	64	9	of	of	ADP
fcis-25709	64	10	the	the	DET
fcis-25709	64	11	decoder	decoder	NOUN
fcis-25709	64	12	path	path	NOUN
fcis-25709	64	13	,	,	PUNCT
fcis-25709	64	14	the	the	DET
fcis-25709	64	15	spatial	spatial	ADJ
fcis-25709	64	16	resolution	resolution	NOUN
fcis-25709	64	17	of	of	ADP
fcis-25709	64	18	the	the	DET
fcis-25709	64	19	feature	feature	NOUN
fcis-25709	64	20	of	of	ADP
fcis-25709	64	21	each	each	DET
fcis-25709	64	22	point	point	NOUN
fcis-25709	64	23	is	be	AUX
fcis-25709	64	24	sympathetically	sympathetically	ADV
fcis-25709	64	25	restored	restore	VERB
fcis-25709	64	26	through	through	ADP
fcis-25709	64	27	the	the	DET
fcis-25709	64	28	nearest	near	ADJ
fcis-25709	64	29	neighbor	neighbor	NOUN
fcis-25709	64	30	interpolation	interpolation	NOUN
fcis-25709	64	31	operation	operation	NOUN
fcis-25709	64	32	in	in	ADP
fcis-25709	64	33	the	the	DET
fcis-25709	64	34	order	order	NOUN
fcis-25709	64	35	of	of	ADP
fcis-25709	64	36	(	(	PUNCT
fcis-25709	64	37	16→32→64→128→256→512	16→32→64→128→256→512	PROPN
fcis-25709	64	38	)	)	PUNCT
fcis-25709	64	39	,	,	PUNCT
fcis-25709	64	40	so	so	SCONJ
fcis-25709	64	41	as	as	SCONJ
fcis-25709	64	42	to	to	PART
fcis-25709	64	43	preserve	preserve	VERB
fcis-25709	64	44	the	the	DET
fcis-25709	64	45	geometric	geometric	ADJ
fcis-25709	64	46	details	detail	NOUN
fcis-25709	64	47	.	.	PUNCT
fcis-25709	65	1	each	each	DET
fcis-25709	65	2	level	level	NOUN
fcis-25709	65	3	of	of	ADP
fcis-25709	65	4	mffm	mffm	NOUN
fcis-25709	65	5	receives	receive	VERB
fcis-25709	65	6	multi	multi	ADJ
fcis-25709	65	7	-	-	ADJ
fcis-25709	65	8	scale	scale	ADJ
fcis-25709	65	9	nested	nest	VERB
fcis-25709	65	10	features	feature	NOUN
fcis-25709	65	11	and	and	CCONJ
fcis-25709	65	12	gradually	gradually	ADV
fcis-25709	65	13	restores	restore	VERB
fcis-25709	65	14	the	the	DET
fcis-25709	65	15	geometric	geometric	ADJ
fcis-25709	65	16	details	detail	NOUN
fcis-25709	65	17	of	of	ADP
fcis-25709	65	18	the	the	DET
fcis-25709	65	19	origin	origin	NOUN
fcis-25709	65	20	features	feature	VERB
fcis-25709	65	21	.	.	PUNCT
fcis-25709	66	1	finally	finally	ADV
fcis-25709	66	2	,	,	PUNCT
fcis-25709	66	3	two	two	NUM
fcis-25709	66	4	shared	share	VERB
fcis-25709	66	5	full	full	ADJ
fcis-25709	66	6	connection	connection	NOUN
fcis-25709	66	7	layers	layer	NOUN
fcis-25709	66	8	are	be	AUX
fcis-25709	66	9	introduced	introduce	VERB
fcis-25709	66	10	to	to	PART
fcis-25709	66	11	map	map	VERB
fcis-25709	66	12	point	point	NOUN
fcis-25709	66	13	features	feature	NOUN
fcis-25709	66	14	to	to	ADP
fcis-25709	66	15	semantic	semantic	ADJ
fcis-25709	66	16	prediction	prediction	NOUN
fcis-25709	66	17	tags	tag	NOUN
fcis-25709	66	18	.	.	PUNCT
fcis-25709	67	1	fundamentally	fundamentally	ADV
fcis-25709	67	2	different	different	ADJ
fcis-25709	67	3	from	from	ADP
fcis-25709	67	4	the	the	DET
fcis-25709	67	5	original	original	ADJ
fcis-25709	67	6	u	u	ADJ
fcis-25709	67	7	-	-	ADJ
fcis-25709	67	8	shaped	shape	VERB
fcis-25709	67	9	architecture	architecture	NOUN
fcis-25709	67	10	with	with	ADP
fcis-25709	67	11	a	a	DET
fcis-25709	67	12	single	single	ADJ
fcis-25709	67	13	coding	code	VERB
fcis-25709	67	14	-	-	PUNCT
fcis-25709	67	15	decoder	decoder	NOUN
fcis-25709	67	16	path	path	NOUN
fcis-25709	67	17	,	,	PUNCT
fcis-25709	67	18	mdnn	mdnn	NOUN
fcis-25709	67	19	further	further	ADJ
fcis-25709	67	20	links	link	NOUN
fcis-25709	67	21	information	information	NOUN
fcis-25709	67	22	flows	flow	NOUN
fcis-25709	67	23	in	in	ADP
fcis-25709	67	24	multiple	multiple	ADJ
fcis-25709	67	25	directions	direction	NOUN
fcis-25709	67	26	and	and	CCONJ
fcis-25709	67	27	scales	scale	NOUN
fcis-25709	67	28	,	,	PUNCT
fcis-25709	67	29	and	and	CCONJ
fcis-25709	67	30	realizes	realize	VERB
fcis-25709	67	31	the	the	DET
fcis-25709	67	32	propagation	propagation	NOUN
fcis-25709	67	33	and	and	CCONJ
fcis-25709	67	34	fusion	fusion	NOUN
fcis-25709	67	35	of	of	ADP
fcis-25709	67	36	multi	multi	ADJ
fcis-25709	67	37	-	-	ADJ
fcis-25709	67	38	scale	scale	ADJ
fcis-25709	67	39	features	feature	NOUN
fcis-25709	67	40	,	,	PUNCT
fcis-25709	67	41	thus	thus	ADV
fcis-25709	67	42	integrating	integrate	VERB
fcis-25709	67	43	richer	rich	ADJ
fcis-25709	67	44	geometric	geometric	ADJ
fcis-25709	67	45	information	information	NOUN
fcis-25709	67	46	(	(	PUNCT
fcis-25709	67	47	such	such	ADJ
fcis-25709	67	48	as	as	ADP
fcis-25709	67	49	edge	edge	NOUN
fcis-25709	67	50	and	and	CCONJ
fcis-25709	67	51	shape	shape	NOUN
fcis-25709	67	52	details	detail	NOUN
fcis-25709	67	53	)	)	PUNCT
fcis-25709	67	54	and	and	CCONJ
fcis-25709	67	55	more	more	ADV
fcis-25709	67	56	abstract	abstract	ADJ
fcis-25709	67	57	semantic	semantic	ADJ
fcis-25709	67	58	information	information	NOUN
fcis-25709	67	59	in	in	ADP
fcis-25709	67	60	the	the	DET
fcis-25709	67	61	point	point	NOUN
fcis-25709	67	62	cloud	cloud	NOUN
fcis-25709	67	63	.	.	PUNCT
fcis-25709	68	1	the	the	DET
fcis-25709	68	2	cross	cross	ADJ
fcis-25709	68	3	-	-	ADJ
fcis-25709	68	4	scale	scale	ADJ
fcis-25709	68	5	information	information	NOUN
fcis-25709	68	6	interaction	interaction	NOUN
fcis-25709	68	7	ability	ability	NOUN
fcis-25709	68	8	of	of	ADP
fcis-25709	68	9	the	the	DET
fcis-25709	68	10	network	network	NOUN
fcis-25709	68	11	is	be	AUX
fcis-25709	68	12	enhanced	enhance	VERB
fcis-25709	68	13	,	,	PUNCT
fcis-25709	68	14	which	which	PRON
fcis-25709	68	15	helps	help	VERB
fcis-25709	68	16	to	to	PART
fcis-25709	68	17	improve	improve	VERB
fcis-25709	68	18	the	the	DET
fcis-25709	68	19	accuracy	accuracy	NOUN
fcis-25709	68	20	of	of	ADP
fcis-25709	68	21	the	the	DET
fcis-25709	68	22	network	network	NOUN
fcis-25709	68	23	model	model	NOUN
fcis-25709	68	24	to	to	ADP
fcis-25709	68	25	the	the	DET
fcis-25709	68	26	point	point	NOUN
fcis-25709	68	27	-	-	PUNCT
fcis-25709	68	28	level	level	NOUN
fcis-25709	68	29	object	object	NOUN
fcis-25709	68	30	segmentation	segmentation	NOUN
fcis-25709	68	31	in	in	ADP
fcis-25709	68	32	the	the	DET
fcis-25709	68	33	face	face	NOUN
fcis-25709	68	34	of	of	ADP
fcis-25709	68	35	complex	complex	ADJ
fcis-25709	68	36	scenes	scene	NOUN
fcis-25709	68	37	.	.	PUNCT
fcis-25709	69	1	13	13	NUM
fcis-25709	69	2	2.2	2.2	NUM
fcis-25709	69	3	.	.	PUNCT
fcis-25709	70	1	multi	multi	ADJ
fcis-25709	70	2	-	-	ADJ
fcis-25709	70	3	scale	scale	ADJ
fcis-25709	70	4	feature	feature	NOUN
fcis-25709	70	5	fusion	fusion	NOUN
fcis-25709	70	6	module	module	NOUN
fcis-25709	70	7	in	in	ADP
fcis-25709	70	8	order	order	NOUN
fcis-25709	70	9	to	to	PART
fcis-25709	70	10	alleviate	alleviate	VERB
fcis-25709	70	11	the	the	DET
fcis-25709	70	12	impact	impact	NOUN
fcis-25709	70	13	of	of	ADP
fcis-25709	70	14	inaccurate	inaccurate	ADJ
fcis-25709	70	15	segmentation	segmentation	NOUN
fcis-25709	70	16	of	of	ADP
fcis-25709	70	17	point	point	NOUN
fcis-25709	70	18	boundaries	boundary	NOUN
fcis-25709	70	19	and	and	CCONJ
fcis-25709	70	20	structural	structural	ADJ
fcis-25709	70	21	details	detail	NOUN
fcis-25709	70	22	caused	cause	VERB
fcis-25709	70	23	by	by	ADP
fcis-25709	70	24	the	the	DET
fcis-25709	70	25	reduction	reduction	NOUN
fcis-25709	70	26	of	of	ADP
fcis-25709	70	27	point	point	NOUN
fcis-25709	70	28	cloud	cloud	NOUN
fcis-25709	70	29	resolution	resolution	NOUN
fcis-25709	70	30	in	in	ADP
fcis-25709	70	31	the	the	DET
fcis-25709	70	32	process	process	NOUN
fcis-25709	70	33	of	of	ADP
fcis-25709	70	34	downsampling	downsampling	NOUN
fcis-25709	70	35	,	,	PUNCT
fcis-25709	70	36	multi	multi	ADJ
fcis-25709	70	37	-	-	ADJ
fcis-25709	70	38	scale	scale	ADJ
fcis-25709	70	39	feature	feature	NOUN
fcis-25709	70	40	fusion	fusion	NOUN
fcis-25709	70	41	modules	module	NOUN
fcis-25709	70	42	are	be	AUX
fcis-25709	70	43	nested	nest	VERB
fcis-25709	70	44	in	in	ADP
fcis-25709	70	45	different	different	ADJ
fcis-25709	70	46	levels	level	NOUN
fcis-25709	70	47	of	of	ADP
fcis-25709	70	48	mdnn	mdnn	NOUN
fcis-25709	70	49	.	.	PUNCT
fcis-25709	71	1	by	by	ADP
fcis-25709	71	2	combining	combine	VERB
fcis-25709	71	3	multiple	multiple	ADJ
fcis-25709	71	4	information	information	NOUN
fcis-25709	71	5	branches	branch	NOUN
fcis-25709	71	6	,	,	PUNCT
fcis-25709	71	7	the	the	DET
fcis-25709	71	8	module	module	NOUN
fcis-25709	71	9	obtains	obtain	VERB
fcis-25709	71	10	high	high	ADJ
fcis-25709	71	11	-	-	PUNCT
fcis-25709	71	12	level	level	NOUN
fcis-25709	71	13	abstract	abstract	ADJ
fcis-25709	71	14	features	feature	NOUN
fcis-25709	71	15	with	with	ADP
fcis-25709	71	16	rich	rich	ADJ
fcis-25709	71	17	semantic	semantic	ADJ
fcis-25709	71	18	representation	representation	NOUN
fcis-25709	71	19	capabilities	capability	NOUN
fcis-25709	71	20	,	,	PUNCT
fcis-25709	71	21	thereby	thereby	ADV
fcis-25709	71	22	improving	improve	VERB
fcis-25709	71	23	semantic	semantic	ADJ
fcis-25709	71	24	consistency	consistency	NOUN
fcis-25709	71	25	and	and	CCONJ
fcis-25709	71	26	realizing	realize	VERB
fcis-25709	71	27	multiscale	multiscale	ADJ
fcis-25709	71	28	information	information	NOUN
fcis-25709	71	29	interaction	interaction	NOUN
fcis-25709	71	30	and	and	CCONJ
fcis-25709	71	31	fusion	fusion	NOUN
fcis-25709	71	32	.	.	PUNCT
fcis-25709	72	1	as	as	SCONJ
fcis-25709	72	2	shown	show	VERB
fcis-25709	72	3	in	in	ADP
fcis-25709	72	4	figure	figure	NOUN
fcis-25709	72	5	2	2	NUM
fcis-25709	72	6	,	,	PUNCT
fcis-25709	72	7	the	the	DET
fcis-25709	72	8	input	input	NOUN
fcis-25709	72	9	is	be	AUX
fcis-25709	72	10	a	a	DET
fcis-25709	72	11	multi	multi	ADJ
fcis-25709	72	12	-	-	ADJ
fcis-25709	72	13	scale	scale	ADJ
fcis-25709	72	14	feature	feature	NOUN
fcis-25709	72	15	with	with	ADP
fcis-25709	72	16	different	different	ADJ
fcis-25709	72	17	feature	feature	NOUN
fcis-25709	72	18	resolutions	resolution	NOUN
fcis-25709	72	19	from	from	ADP
fcis-25709	72	20	its	its	PRON
fcis-25709	72	21	previous	previous	ADJ
fcis-25709	72	22	block	block	NOUN
fcis-25709	72	23	.	.	PUNCT
fcis-25709	73	1	fig	fig	NOUN
fcis-25709	73	2	2	2	NUM
fcis-25709	73	3	.	.	PUNCT
fcis-25709	74	1	multi	multi	ADJ
fcis-25709	74	2	-	-	ADJ
fcis-25709	74	3	scale	scale	ADJ
fcis-25709	74	4	feature	feature	NOUN
fcis-25709	74	5	fusion	fusion	NOUN
fcis-25709	74	6	module	module	NOUN
fcis-25709	74	7	take	take	VERB
fcis-25709	74	8	the	the	DET
fcis-25709	74	9	feature	feature	NOUN
fcis-25709	74	10	fusion	fusion	NOUN
fcis-25709	74	11	module	module	NOUN
fcis-25709	74	12	of	of	ADP
fcis-25709	74	13			PROPN
fcis-25709	74	14			PROPN
fcis-25709	74	15	,	,	PUNCT
fcis-25709	74	16	0i	0i	NOUN
fcis-25709	74	17	jf	jf	PROPN
fcis-25709	75	1	i	i	PRON
fcis-25709	75	2			VERB
fcis-25709	75	3	as	as	ADP
fcis-25709	75	4	an	an	DET
fcis-25709	75	5	example	example	NOUN
fcis-25709	75	6	,	,	PUNCT
fcis-25709	75	7	first	first	ADV
fcis-25709	75	8	,	,	PUNCT
fcis-25709	75	9	it	it	PRON
fcis-25709	75	10	receives	receive	VERB
fcis-25709	75	11	the	the	DET
fcis-25709	75	12	subsampled	subsample	VERB
fcis-25709	75	13	data	datum	NOUN
fcis-25709	75	14	af	af	PROPN
fcis-25709	75	15	,	,	PUNCT
fcis-25709	75	16	the	the	DET
fcis-25709	75	17	same	same	ADJ
fcis-25709	75	18	resolution	resolution	NOUN
fcis-25709	75	19	data	datum	NOUN
fcis-25709	75	20	bf	bf	NOUN
fcis-25709	75	21	from	from	ADP
fcis-25709	75	22	horizontal	horizontal	ADJ
fcis-25709	75	23	transmission	transmission	NOUN
fcis-25709	75	24	,	,	PUNCT
fcis-25709	75	25	and	and	CCONJ
fcis-25709	75	26	the	the	DET
fcis-25709	75	27	upsampled	upsample	VERB
fcis-25709	75	28	data	data	NOUN
fcis-25709	75	29	cf	cf	NOUN
fcis-25709	75	30	,	,	PUNCT
fcis-25709	75	31	from	from	ADP
fcis-25709	75	32	vertical	vertical	ADJ
fcis-25709	75	33	transmission	transmission	NOUN
fcis-25709	75	34	,	,	PUNCT
fcis-25709	75	35	which	which	PRON
fcis-25709	75	36	can	can	AUX
fcis-25709	75	37	be	be	AUX
fcis-25709	75	38	expressed	express	VERB
fcis-25709	75	39	as	as	ADP
fcis-25709	75	40	:	:	PUNCT
fcis-25709	75	41			PROPN
fcis-25709	75	42	1	1	NOUN
fcis-25709	75	43	,	,	PUNCT
fcis-25709	75	44	1a	1a	PROPN
fcis-25709	76	1	i	i	PRON
fcis-25709	76	2	jf	jf	PROPN
fcis-25709	77	1	d	d	PROPN
fcis-25709	77	2	f	f	PROPN
fcis-25709	77	3			PROPN
fcis-25709	77	4			PROPN
fcis-25709	77	5	(	(	PUNCT
fcis-25709	77	6	2	2	NUM
fcis-25709	77	7	)	)	PUNCT
fcis-25709	77	8	,	,	PUNCT
fcis-25709	77	9	1b	1b	NUM
fcis-25709	78	1	i	i	PRON
fcis-25709	78	2	jf	jf	PROPN
fcis-25709	78	3	f	f	PROPN
fcis-25709	78	4			PROPN
fcis-25709	78	5	(	(	PUNCT
fcis-25709	78	6	3	3	NUM
fcis-25709	78	7	)	)	PUNCT
fcis-25709	78	8			NOUN
fcis-25709	78	9	1,c	1,c	ADP
fcis-25709	79	1	i	i	PRON
fcis-25709	79	2	jf	jf	VERB
fcis-25709	79	3	u	u	NOUN
fcis-25709	79	4	f	f	PROPN
fcis-25709	79	5			PROPN
fcis-25709	79	6	(	(	PUNCT
fcis-25709	79	7	4	4	NUM
fcis-25709	79	8	)	)	PUNCT
fcis-25709	79	9	secondly	secondly	ADV
fcis-25709	79	10	,	,	PUNCT
fcis-25709	79	11	the	the	DET
fcis-25709	79	12	feature	feature	NOUN
fcis-25709	79	13	channels	channel	NOUN
fcis-25709	79	14	of	of	ADP
fcis-25709	79	15	the	the	DET
fcis-25709	79	16	three	three	NUM
fcis-25709	79	17	scales	scale	NOUN
fcis-25709	79	18	are	be	AUX
fcis-25709	79	19	squeezed	squeeze	VERB
fcis-25709	79	20	into	into	ADP
fcis-25709	79	21	the	the	DET
fcis-25709	79	22	same	same	ADJ
fcis-25709	79	23	dimension	dimension	NOUN
fcis-25709	79	24	,	,	PUNCT
fcis-25709	79	25	and	and	CCONJ
fcis-25709	79	26	the	the	DET
fcis-25709	79	27	features	feature	NOUN
fcis-25709	79	28	of	of	ADP
fcis-25709	79	29	different	different	ADJ
fcis-25709	79	30	layers	layer	NOUN
fcis-25709	79	31	are	be	AUX
fcis-25709	79	32	reused	reuse	VERB
fcis-25709	79	33	for	for	ADP
fcis-25709	79	34	fusion	fusion	NOUN
fcis-25709	79	35	transformation	transformation	NOUN
fcis-25709	79	36	to	to	PART
fcis-25709	79	37	obtain	obtain	VERB
fcis-25709	79	38	the	the	DET
fcis-25709	79	39	transform	transform	NOUN
fcis-25709	79	40	features	feature	NOUN
fcis-25709	79	41	t	t	PROPN
fcis-25709	79	42	af	af	PROPN
fcis-25709	79	43	,	,	PUNCT
fcis-25709	79	44	t	t	NOUN
fcis-25709	79	45	bf	bf	NOUN
fcis-25709	80	1	and	and	CCONJ
fcis-25709	80	2	t	t	PROPN
fcis-25709	80	3	cf	cf	NOUN
fcis-25709	80	4	,	,	PUNCT
fcis-25709	80	5	which	which	PRON
fcis-25709	80	6	can	can	AUX
fcis-25709	80	7	be	be	AUX
fcis-25709	80	8	expressed	express	VERB
fcis-25709	80	9	as	as	ADP
fcis-25709	80	10	:	:	PUNCT
fcis-25709	80	11			NOUN
fcis-25709	80	12			PROPN
fcis-25709	80	13			NOUN
fcis-25709	80	14			NOUN
fcis-25709	80	15	t	t	VERB
fcis-25709	81	1	a	a	DET
fcis-25709	81	2	a	a	DET
fcis-25709	81	3	a	a	DET
fcis-25709	81	4	bf	bf	NOUN
fcis-25709	81	5	f	f	PROPN
fcis-25709	81	6	mp	mp	PROPN
fcis-25709	81	7	f	f	PROPN
fcis-25709	81	8	mp	mp	PROPN
fcis-25709	81	9	f	f	PROPN
fcis-25709	81	10			PROPN
fcis-25709	81	11	(	(	PUNCT
fcis-25709	81	12	5	5	NUM
fcis-25709	81	13	)	)	PUNCT
fcis-25709	81	14			NOUN
fcis-25709	81	15	t	t	NOUN
fcis-25709	81	16	b	b	NOUN
fcis-25709	81	17	bf	bf	NOUN
fcis-25709	81	18	lfau	lfau	NOUN
fcis-25709	81	19	f	f	PROPN
fcis-25709	81	20	(	(	PUNCT
fcis-25709	81	21	6	6	NUM
fcis-25709	81	22	)	)	PUNCT
fcis-25709	81	23			NOUN
fcis-25709	81	24			SYM
fcis-25709	81	25			NOUN
fcis-25709	81	26			NOUN
fcis-25709	81	27	t	t	PROPN
fcis-25709	81	28	c	c	PROPN
fcis-25709	81	29	c	c	PROPN
fcis-25709	81	30	b	b	X
fcis-25709	81	31	cf	cf	X
fcis-25709	81	32	f	f	PROPN
fcis-25709	81	33	mp	mp	PROPN
fcis-25709	81	34	f	f	PROPN
fcis-25709	81	35	mp	mp	PROPN
fcis-25709	81	36	f	f	NOUN
fcis-25709	81	37			PROPN
fcis-25709	81	38			PROPN
fcis-25709	81	39	(	(	PUNCT
fcis-25709	81	40	7	7	NUM
fcis-25709	81	41	)	)	PUNCT
fcis-25709	81	42	where	where	SCONJ
fcis-25709	81	43	,	,	PUNCT
fcis-25709	81	44			PROPN
fcis-25709	81	45	is	be	AUX
fcis-25709	81	46	dot	dot	NOUN
fcis-25709	81	47	product	product	NOUN
fcis-25709	81	48	,	,	PUNCT
fcis-25709	81	49			PROPN
fcis-25709	81	50	is	be	AUX
fcis-25709	81	51	addition	addition	NOUN
fcis-25709	81	52	,	,	PUNCT
fcis-25709	81	53			PROPN
fcis-25709	81	54	is	be	AUX
fcis-25709	81	55	sigmoid	sigmoid	NOUN
fcis-25709	81	56	activation	activation	NOUN
fcis-25709	81	57	function	function	NOUN
fcis-25709	81	58	,	,	PUNCT
fcis-25709	81	59	mp	mp	PROPN
fcis-25709	81	60	is	be	AUX
fcis-25709	81	61	maxpooling	maxpoole	VERB
fcis-25709	81	62	,	,	PUNCT
fcis-25709	81	63	lfau	lfau	PROPN
fcis-25709	81	64	is	be	AUX
fcis-25709	81	65	local	local	ADJ
fcis-25709	81	66	feature	feature	NOUN
fcis-25709	81	67	aggregation	aggregation	NOUN
fcis-25709	81	68	unit(lfau	unit(lfau	PROPN
fcis-25709	81	69	)	)	PUNCT
fcis-25709	81	70	.	.	PUNCT
fcis-25709	82	1	then	then	ADV
fcis-25709	82	2	,	,	PUNCT
fcis-25709	82	3	the	the	DET
fcis-25709	82	4	transformation	transformation	NOUN
fcis-25709	82	5	features	feature	NOUN
fcis-25709	82	6	are	be	AUX
fcis-25709	82	7	fused	fuse	VERB
fcis-25709	82	8	and	and	CCONJ
fcis-25709	82	9	spliced	splice	VERB
fcis-25709	82	10	.	.	PUNCT
fcis-25709	83	1	finally	finally	ADV
fcis-25709	83	2	,	,	PUNCT
fcis-25709	83	3	mlp	mlp	PROPN
fcis-25709	83	4	is	be	AUX
fcis-25709	83	5	used	use	VERB
fcis-25709	83	6	to	to	PART
fcis-25709	83	7	reduce	reduce	VERB
fcis-25709	83	8	the	the	DET
fcis-25709	83	9	channels	channel	NOUN
fcis-25709	83	10	of	of	ADP
fcis-25709	83	11	stacked	stack	VERB
fcis-25709	83	12	features	feature	NOUN
fcis-25709	83	13	,	,	PUNCT
fcis-25709	83	14	so	so	SCONJ
fcis-25709	83	15	as	as	SCONJ
fcis-25709	83	16	to	to	PART
fcis-25709	83	17	output	output	VERB
fcis-25709	83	18	fusion	fusion	NOUN
fcis-25709	83	19	feature	feature	NOUN
fcis-25709	83	20	outf	outf	NOUN
fcis-25709	83	21	.	.	PUNCT
fcis-25709	84	1	the	the	DET
fcis-25709	84	2	multi	multi	ADJ
fcis-25709	84	3	-	-	ADJ
fcis-25709	84	4	scale	scale	ADJ
fcis-25709	84	5	feature	feature	NOUN
fcis-25709	84	6	fusion	fusion	NOUN
fcis-25709	84	7	process	process	NOUN
fcis-25709	84	8	can	can	AUX
fcis-25709	84	9	be	be	AUX
fcis-25709	84	10	expressed	express	VERB
fcis-25709	84	11	as	as	ADP
fcis-25709	84	12	:	:	PUNCT
fcis-25709	84	13			PROPN
fcis-25709	84	14			PROPN
fcis-25709	84	15	,	,	PUNCT
fcis-25709	84	16	,	,	PUNCT
fcis-25709	84	17	t	t	PROPN
fcis-25709	84	18	t	t	PROPN
fcis-25709	84	19	t	t	PROPN
fcis-25709	84	20	out	out	ADP
fcis-25709	84	21	a	a	DET
fcis-25709	84	22	b	b	NOUN
fcis-25709	84	23	cf	cf	NOUN
fcis-25709	84	24	mlp	mlp	PROPN
fcis-25709	84	25	f	f	PROPN
fcis-25709	84	26	f	f	PROPN
fcis-25709	84	27	f	f	PROPN
fcis-25709	84	28			PROPN
fcis-25709	84	29			PROPN
fcis-25709	84	30			PROPN
fcis-25709	84	31	(	(	PUNCT
fcis-25709	84	32	8)	8)	NUM
fcis-25709	84	33	where	where	SCONJ
fcis-25709	84	34	,	,	PUNCT
fcis-25709	84	35	mlp	mlp	PROPN
fcis-25709	84	36	is	be	AUX
fcis-25709	84	37	the	the	DET
fcis-25709	84	38	shared	share	VERB
fcis-25709	84	39	fully	fully	ADV
fcis-25709	84	40	connected	connect	VERB
fcis-25709	84	41	layer	layer	NOUN
fcis-25709	84	42	,	,	PUNCT
fcis-25709	84	43	and	and	CCONJ
fcis-25709	84	44			PROPN
fcis-25709	84	45			PROPN
fcis-25709	84	46	,	,	PUNCT
fcis-25709	84	47	is	be	AUX
fcis-25709	84	48	the	the	DET
fcis-25709	84	49	feature	feature	NOUN
fcis-25709	84	50	splicing	splicing	NOUN
fcis-25709	84	51	.	.	PUNCT
fcis-25709	85	1	in	in	ADP
fcis-25709	85	2	order	order	NOUN
fcis-25709	85	3	to	to	PART
fcis-25709	85	4	capture	capture	VERB
fcis-25709	85	5	local	local	ADJ
fcis-25709	85	6	features	feature	NOUN
fcis-25709	85	7	of	of	ADP
fcis-25709	85	8	cross	cross	ADJ
fcis-25709	85	9	-	-	ADJ
fcis-25709	85	10	scale	scale	ADJ
fcis-25709	85	11	sampling	sampling	NOUN
fcis-25709	85	12	points	point	NOUN
fcis-25709	85	13	at	at	ADP
fcis-25709	85	14	different	different	ADJ
fcis-25709	85	15	depths	depth	NOUN
fcis-25709	85	16	,	,	PUNCT
fcis-25709	85	17	lfau	lfau	PROPN
fcis-25709	85	18	is	be	AUX
fcis-25709	85	19	used	use	VERB
fcis-25709	85	20	as	as	ADP
fcis-25709	85	21	the	the	DET
fcis-25709	85	22	basic	basic	ADJ
fcis-25709	85	23	feature	feature	NOUN
fcis-25709	85	24	extraction	extraction	NOUN
fcis-25709	85	25	unit	unit	NOUN
fcis-25709	85	26	in	in	ADP
fcis-25709	85	27	mffm	mffm	NOUN
fcis-25709	85	28	.	.	PUNCT
fcis-25709	86	1	as	as	SCONJ
fcis-25709	86	2	shown	show	VERB
fcis-25709	86	3	in	in	ADP
fcis-25709	86	4	figure	figure	NOUN
fcis-25709	86	5	3	3	NUM
fcis-25709	86	6	,	,	PUNCT
fcis-25709	86	7	lfau	lfau	NOUN
fcis-25709	86	8	is	be	AUX
fcis-25709	86	9	mainly	mainly	ADV
fcis-25709	86	10	composed	compose	VERB
fcis-25709	86	11	of	of	ADP
fcis-25709	86	12	two	two	NUM
fcis-25709	86	13	feature	feature	NOUN
fcis-25709	86	14	graph	graph	NOUN
fcis-25709	86	15	convolution	convolution	NOUN
fcis-25709	86	16	operators	operator	NOUN
fcis-25709	86	17	(	(	PUNCT
fcis-25709	86	18	fgco	fgco	PROPN
fcis-25709	86	19	)	)	PUNCT
fcis-25709	86	20	and	and	CCONJ
fcis-25709	86	21	two	two	NUM
fcis-25709	86	22	attention	attention	NOUN
fcis-25709	86	23	pooling	pool	VERB
fcis-25709	86	24	layers	layer	NOUN
fcis-25709	86	25	(	(	PUNCT
fcis-25709	86	26	apl	apl	PROPN
fcis-25709	86	27	)	)	PUNCT
fcis-25709	86	28	.	.	PUNCT
fcis-25709	87	1	before	before	ADP
fcis-25709	87	2	each	each	DET
fcis-25709	87	3	fgco	fgco	NOUN
fcis-25709	87	4	,	,	PUNCT
fcis-25709	87	5	the	the	DET
fcis-25709	87	6	three	three	NUM
fcis-25709	87	7	-	-	PUNCT
fcis-25709	87	8	dimensional	dimensional	ADJ
fcis-25709	87	9	spatial	spatial	ADJ
fcis-25709	87	10	coordinates	coordinate	NOUN
fcis-25709	87	11	of	of	ADP
fcis-25709	87	12	the	the	DET
fcis-25709	87	13	point	point	NOUN
fcis-25709	87	14	cloud	cloud	NOUN
fcis-25709	87	15	were	be	AUX
fcis-25709	87	16	entered	enter	VERB
fcis-25709	87	17	into	into	ADP
fcis-25709	87	18	the	the	DET
fcis-25709	87	19	graph	graph	NOUN
fcis-25709	87	20	convolution	convolution	NOUN
fcis-25709	87	21	operator	operator	NOUN
fcis-25709	87	22	together	together	ADV
fcis-25709	87	23	with	with	ADP
fcis-25709	87	24	the	the	DET
fcis-25709	87	25	original	original	ADJ
fcis-25709	87	26	position	position	NOUN
fcis-25709	87	27	features	feature	NOUN
fcis-25709	87	28	and	and	CCONJ
fcis-25709	87	29	the	the	DET
fcis-25709	87	30	input	input	NOUN
fcis-25709	87	31	point	point	NOUN
fcis-25709	87	32	features	feature	VERB
fcis-25709	87	33	for	for	ADP
fcis-25709	87	34	relative	relative	ADJ
fcis-25709	87	35	position	position	NOUN
fcis-25709	87	36	coding	coding	NOUN
fcis-25709	87	37	,	,	PUNCT
fcis-25709	87	38	so	so	SCONJ
fcis-25709	87	39	as	as	SCONJ
fcis-25709	87	40	to	to	PART
fcis-25709	87	41	reuse	reuse	VERB
fcis-25709	87	42	the	the	DET
fcis-25709	87	43	overall	overall	ADJ
fcis-25709	87	44	morphological	morphological	ADJ
fcis-25709	87	45	information	information	NOUN
fcis-25709	87	46	and	and	CCONJ
fcis-25709	87	47	enhance	enhance	VERB
fcis-25709	87	48	the	the	DET
fcis-25709	87	49	module	module	NOUN
fcis-25709	87	50	's	's	PART
fcis-25709	87	51	ability	ability	NOUN
fcis-25709	87	52	to	to	PART
fcis-25709	87	53	capture	capture	VERB
fcis-25709	87	54	local	local	ADJ
fcis-25709	87	55	spatial	spatial	ADJ
fcis-25709	87	56	details	detail	NOUN
fcis-25709	87	57	and	and	CCONJ
fcis-25709	87	58	semantic	semantic	ADJ
fcis-25709	87	59	information	information	NOUN
fcis-25709	87	60	.	.	PUNCT
fcis-25709	88	1	to	to	PART
fcis-25709	88	2	more	more	ADV
fcis-25709	88	3	fully	fully	ADV
fcis-25709	88	4	capture	capture	VERB
fcis-25709	88	5	the	the	DET
fcis-25709	88	6	detail	detail	NOUN
fcis-25709	88	7	and	and	CCONJ
fcis-25709	88	8	complexity	complexity	NOUN
fcis-25709	88	9	of	of	ADP
fcis-25709	88	10	point	point	NOUN
fcis-25709	88	11	cloud	cloud	NOUN
fcis-25709	88	12	data	datum	NOUN
fcis-25709	88	13	,	,	PUNCT
fcis-25709	88	14	a	a	DET
fcis-25709	88	15	dense	dense	ADJ
fcis-25709	88	16	skip	skip	ADJ
fcis-25709	88	17	connection	connection	NOUN
fcis-25709	88	18	(	(	PUNCT
fcis-25709	88	19	dsc	dsc	NOUN
fcis-25709	88	20	)	)	PUNCT
fcis-25709	88	21	is	be	AUX
fcis-25709	88	22	used	use	VERB
fcis-25709	88	23	to	to	PART
fcis-25709	88	24	connect	connect	VERB
fcis-25709	88	25	two	two	NUM
fcis-25709	88	26	fgco	fgco	NOUN
fcis-25709	88	27	and	and	CCONJ
fcis-25709	88	28	apl	apl	NOUN
fcis-25709	88	29	after	after	ADP
fcis-25709	88	30	sharing	share	VERB
fcis-25709	88	31	the	the	DET
fcis-25709	88	32	full	full	ADJ
fcis-25709	88	33	connection	connection	NOUN
fcis-25709	88	34	layer	layer	NOUN
fcis-25709	88	35	for	for	ADP
fcis-25709	88	36	more	more	ADV
fcis-25709	88	37	efficient	efficient	ADJ
fcis-25709	88	38	feature	feature	NOUN
fcis-25709	88	39	propagation	propagation	NOUN
fcis-25709	88	40	.	.	PUNCT
fcis-25709	89	1	fig	fig	NOUN
fcis-25709	89	2	3	3	NUM
fcis-25709	89	3	.	.	PUNCT
fcis-25709	90	1	local	local	ADJ
fcis-25709	90	2	feature	feature	NOUN
fcis-25709	90	3	aggregation	aggregation	NOUN
fcis-25709	90	4	unit	unit	NOUN
fcis-25709	90	5	the	the	DET
fcis-25709	90	6	details	detail	NOUN
fcis-25709	90	7	of	of	ADP
fcis-25709	90	8	fgco	fgco	NOUN
fcis-25709	90	9	are	be	AUX
fcis-25709	90	10	shown	show	VERB
fcis-25709	90	11	in	in	ADP
fcis-25709	90	12	figure	figure	NOUN
fcis-25709	90	13	4	4	NUM
fcis-25709	90	14	,	,	PUNCT
fcis-25709	90	15	where	where	SCONJ
fcis-25709	90	16	the	the	DET
fcis-25709	90	17	key	key	ADJ
fcis-25709	90	18	step	step	NOUN
fcis-25709	90	19	is	be	AUX
fcis-25709	90	20	the	the	DET
fcis-25709	90	21	construction	construction	NOUN
fcis-25709	90	22	of	of	ADP
fcis-25709	90	23	the	the	DET
fcis-25709	90	24	local	local	ADJ
fcis-25709	90	25	neighborhood	neighborhood	NOUN
fcis-25709	90	26	map	map	NOUN
fcis-25709	90	27	.	.	PUNCT
fcis-25709	91	1	for	for	ADP
fcis-25709	91	2	an	an	DET
fcis-25709	91	3	unordered	unordered	ADJ
fcis-25709	91	4	point	point	NOUN
fcis-25709	91	5	cluster	cluster	NOUN
fcis-25709	91	6	with	with	ADP
fcis-25709	91	7	n	n	NUM
fcis-25709	91	8	points	point	NOUN
fcis-25709	91	9	,	,	PUNCT
fcis-25709	91	10	it	it	PRON
fcis-25709	91	11	can	can	AUX
fcis-25709	91	12	be	be	AUX
fcis-25709	91	13	defined	define	VERB
fcis-25709	91	14	as	as	ADP
fcis-25709	91	15	:	:	PUNCT
fcis-25709	91	16			NOUN
fcis-25709	91	17	1	1	NOUN
fcis-25709	91	18	2	2	NUM
fcis-25709	91	19	,	,	PUNCT
fcis-25709	91	20	,	,	PUNCT
fcis-25709	91	21	,	,	PUNCT
fcis-25709	92	1	d	d	X
fcis-25709	92	2	np	np	INTJ
fcis-25709	93	1	p	p	X
fcis-25709	93	2	p	p	X
fcis-25709	93	3	p	p	X
fcis-25709	93	4	r	r	NOUN
fcis-25709	93	5			PROPN
fcis-25709	93	6	,	,	PUNCT
fcis-25709	93	7	dimension	dimension	NOUN
fcis-25709	93	8	d	d	NOUN
fcis-25709	93	9	is	be	AUX
fcis-25709	93	10	generically	generically	ADV
fcis-25709	93	11	expressed	express	VERB
fcis-25709	93	12	as	as	ADP
fcis-25709	93	13	the	the	DET
fcis-25709	93	14	characteristic	characteristic	ADJ
fcis-25709	93	15	dimension	dimension	NOUN
fcis-25709	93	16	of	of	ADP
fcis-25709	93	17	a	a	DET
fcis-25709	93	18	certain	certain	ADJ
fcis-25709	93	19	layer	layer	NOUN
fcis-25709	93	20	.	.	PUNCT
fcis-25709	94	1	the	the	DET
fcis-25709	94	2	point	point	NOUN
fcis-25709	94	3	characteristics	characteristic	NOUN
fcis-25709	94	4	corresponding	correspond	VERB
fcis-25709	94	5	to	to	ADP
fcis-25709	94	6	the	the	DET
fcis-25709	94	7	point	point	NOUN
fcis-25709	94	8	convergence	convergence	NOUN
fcis-25709	94	9	are	be	AUX
fcis-25709	94	10	:	:	PUNCT
fcis-25709	94	11			NOUN
fcis-25709	94	12	1	1	NOUN
fcis-25709	94	13	2	2	NUM
fcis-25709	94	14	,	,	PUNCT
fcis-25709	94	15	,	,	PUNCT
fcis-25709	94	16	,	,	PUNCT
fcis-25709	94	17	n	n	PROPN
fcis-25709	94	18	d	d	NOUN
fcis-25709	94	19	p	p	NOUN
fcis-25709	95	1	nf	nf	INTJ
fcis-25709	95	2	f	f	NOUN
fcis-25709	95	3	f	f	NOUN
fcis-25709	95	4	f	f	PROPN
fcis-25709	95	5	r	r	NOUN
fcis-25709	95	6			NOUN
fcis-25709	95	7			PROPN
fcis-25709	95	8	.	.	PUNCT
fcis-25709	96	1	first	first	ADV
fcis-25709	96	2	,	,	PUNCT
fcis-25709	96	3	in	in	ADP
fcis-25709	96	4	the	the	DET
fcis-25709	96	5	process	process	NOUN
fcis-25709	96	6	of	of	ADP
fcis-25709	96	7	constructing	construct	VERB
fcis-25709	96	8	the	the	DET
fcis-25709	96	9	spatial	spatial	ADJ
fcis-25709	96	10	domain	domain	NOUN
fcis-25709	96	11	of	of	ADP
fcis-25709	96	12	the	the	DET
fcis-25709	96	13	neighborhood	neighborhood	NOUN
fcis-25709	96	14	graph	graph	NOUN
fcis-25709	96	15	,	,	PUNCT
fcis-25709	96	16	the	the	DET
fcis-25709	96	17	center	center	NOUN
fcis-25709	96	18	point	point	NOUN
fcis-25709	96	19	for	for	ADP
fcis-25709	96	20	each	each	DET
fcis-25709	96	21	input	input	NOUN
fcis-25709	96	22	is	be	AUX
fcis-25709	96	23	determined	determine	VERB
fcis-25709	96	24	ip	ip	ADP
fcis-25709	96	25	,	,	PUNCT
fcis-25709	96	26	fgco	fgco	PROPN
fcis-25709	96	27	calculates	calculate	VERB
fcis-25709	96	28	the	the	DET
fcis-25709	96	29	distance	distance	NOUN
fcis-25709	96	30	on	on	ADP
fcis-25709	96	31	euclidean	euclidean	ADJ
fcis-25709	96	32	space	space	NOUN
fcis-25709	96	33	based	base	VERB
fcis-25709	96	34	on	on	ADP
fcis-25709	96	35	the	the	DET
fcis-25709	96	36	k	k	PROPN
fcis-25709	96	37	-	-	PUNCT
fcis-25709	96	38	nearest	near	ADJ
fcis-25709	96	39	neighbor	neighbor	NOUN
fcis-25709	96	40	algorithm	algorithm	NOUN
fcis-25709	96	41	,	,	PUNCT
fcis-25709	96	42	and	and	CCONJ
fcis-25709	96	43	selects	select	VERB
fcis-25709	96	44	14	14	NUM
fcis-25709	96	45	the	the	DET
fcis-25709	96	46	k	k	PROPN
fcis-25709	96	47	neighbor	neighbor	NOUN
fcis-25709	96	48	node	node	PROPN
fcis-25709	96	49			PROPN
fcis-25709	96	50	3	3	PROPN
fcis-25709	96	51	1,2	1,2	NUM
fcis-25709	96	52	,	,	PUNCT
fcis-25709	96	53	,	,	PUNCT
fcis-25709	96	54	n	n	PROPN
fcis-25709	96	55	k	k	NOUN
fcis-25709	96	56	ijp	ijp	ADV
fcis-25709	96	57	p	p	PROPN
fcis-25709	96	58	r	r	PROPN
fcis-25709	96	59	j	j	PROPN
fcis-25709	96	60	k	k	PROPN
fcis-25709	96	61			PROPN
fcis-25709	96	62			NUM
fcis-25709	96	63			NUM
fcis-25709	96	64	closest	close	ADJ
fcis-25709	96	65	to	to	PART
fcis-25709	96	66	point	point	VERB
fcis-25709	96	67	ip	ip	NOUN
fcis-25709	96	68	and	and	CCONJ
fcis-25709	96	69	its	its	PRON
fcis-25709	96	70	corresponding	corresponding	ADJ
fcis-25709	96	71	neighbor	neighbor	NOUN
fcis-25709	96	72	node	node	NOUN
fcis-25709	96	73	features	feature	VERB
fcis-25709	96	74			PROPN
fcis-25709	96	75	1,2	1,2	PROPN
fcis-25709	96	76	,	,	PUNCT
fcis-25709	96	77	,	,	PUNCT
fcis-25709	96	78	n	n	PROPN
fcis-25709	96	79	d	d	X
fcis-25709	96	80	k	k	X
fcis-25709	97	1	ijf	ijf	X
fcis-25709	97	2	f	f	PROPN
fcis-25709	97	3	r	r	NOUN
fcis-25709	97	4	j	j	PROPN
fcis-25709	97	5	k	k	PROPN
fcis-25709	97	6			PROPN
fcis-25709	97	7			NUM
fcis-25709	98	1			NOUN
fcis-25709	98	2	.	.	PUNCT
fcis-25709	99	1	fig	fig	NOUN
fcis-25709	99	2	4	4	NUM
fcis-25709	99	3	.	.	PUNCT
fcis-25709	99	4	feature	feature	NOUN
fcis-25709	99	5	map	map	NOUN
fcis-25709	99	6	convolution	convolution	NOUN
fcis-25709	99	7	operator	operator	NOUN
fcis-25709	99	8	and	and	CCONJ
fcis-25709	99	9	attention	attention	NOUN
fcis-25709	99	10	pooling	pool	VERB
fcis-25709	99	11	layer	layer	NOUN
fcis-25709	99	12	details	detail	NOUN
fcis-25709	99	13	secondly	secondly	ADV
fcis-25709	99	14	,	,	PUNCT
fcis-25709	99	15	a	a	DET
fcis-25709	99	16	spatial	spatial	ADJ
fcis-25709	99	17	relationship	relationship	NOUN
fcis-25709	99	18	is	be	AUX
fcis-25709	99	19	established	establish	VERB
fcis-25709	99	20	for	for	ADP
fcis-25709	99	21	the	the	DET
fcis-25709	99	22	distance	distance	NOUN
fcis-25709	99	23	and	and	CCONJ
fcis-25709	99	24	direction	direction	NOUN
fcis-25709	99	25	relationship	relationship	NOUN
fcis-25709	99	26	between	between	ADP
fcis-25709	99	27	each	each	DET
fcis-25709	99	28	point	point	NOUN
fcis-25709	99	29	ip	ip	NOUN
fcis-25709	99	30	and	and	CCONJ
fcis-25709	99	31	its	its	PRON
fcis-25709	99	32	k	k	PROPN
fcis-25709	99	33	nearest	near	ADJ
fcis-25709	99	34	neighbor	neighbor	PROPN
fcis-25709	99	35	node	node	PROPN
fcis-25709	99	36	kp	kp	PROPN
fcis-25709	99	37	,	,	PUNCT
fcis-25709	99	38	and	and	CCONJ
fcis-25709	99	39	a	a	DET
fcis-25709	99	40	directed	direct	VERB
fcis-25709	99	41	graph	graph	NOUN
fcis-25709	99	42	ig	ig	PROPN
fcis-25709	99	43	is	be	AUX
fcis-25709	99	44	used	use	VERB
fcis-25709	99	45	to	to	PART
fcis-25709	99	46	implicitly	implicitly	ADV
fcis-25709	99	47	represent	represent	VERB
fcis-25709	99	48	the	the	DET
fcis-25709	99	49	local	local	ADJ
fcis-25709	99	50	structure	structure	NOUN
fcis-25709	99	51	of	of	ADP
fcis-25709	99	52	the	the	DET
fcis-25709	99	53	point	point	NOUN
fcis-25709	99	54	cloud	cloud	NOUN
fcis-25709	99	55	,	,	PUNCT
fcis-25709	99	56	as	as	SCONJ
fcis-25709	99	57	shown	show	VERB
fcis-25709	99	58	in	in	ADP
fcis-25709	99	59	formula	formula	NOUN
fcis-25709	99	60	(	(	PUNCT
fcis-25709	99	61	9	9	NUM
fcis-25709	99	62	)	)	PUNCT
fcis-25709	99	63	:	:	PUNCT
fcis-25709	99	64			NOUN
fcis-25709	99	65			PUNCT
fcis-25709	100	1			PROPN
fcis-25709	101	1			PROPN
fcis-25709	101	2			NOUN
fcis-25709	101	3			NOUN
fcis-25709	101	4			PROPN
fcis-25709	101	5	,	,	PUNCT
fcis-25709	101	6	1,2	1,2	NUM
fcis-25709	101	7	,	,	PUNCT
fcis-25709	101	8	1,2	1,2	NUM
fcis-25709	101	9	,	,	PUNCT
fcis-25709	102	1	i	i	PRON
fcis-25709	102	2	i	i	VERB
fcis-25709	103	1	i	i	VERB
fcis-25709	103	2	n	n	VERB
fcis-25709	104	1	d	d	NOUN
fcis-25709	104	2	i	i	PRON
fcis-25709	105	1	ij	ij	INTJ
fcis-25709	106	1	i	i	PRON
fcis-25709	107	1	n	n	NOUN
fcis-25709	108	1	d	d	NOUN
fcis-25709	109	1	i	i	PRON
fcis-25709	110	1	ij	ij	INTJ
fcis-25709	111	1	ij	ij	INTJ
fcis-25709	112	1	i	i	PRON
fcis-25709	112	2	g	g	VERB
fcis-25709	112	3	v	v	ADP
fcis-25709	112	4	e	e	X
fcis-25709	112	5	v	v	NOUN
fcis-25709	112	6	f	f	X
fcis-25709	112	7	f	f	PROPN
fcis-25709	112	8	r	r	NOUN
fcis-25709	112	9	j	j	PROPN
fcis-25709	112	10	k	k	PROPN
fcis-25709	112	11	e	e	PROPN
fcis-25709	112	12	e	e	X
fcis-25709	112	13	g	g	PROPN
fcis-25709	112	14	f	f	PROPN
fcis-25709	112	15	f	f	PROPN
fcis-25709	112	16	r	r	NOUN
fcis-25709	112	17	j	j	PROPN
fcis-25709	112	18	k	k	PROPN
fcis-25709	112	19			AUX
fcis-25709	112	20			PROPN
fcis-25709	112	21			NOUN
fcis-25709	112	22			PROPN
fcis-25709	112	23			NUM
fcis-25709	112	24			PROPN
fcis-25709	112	25			PROPN
fcis-25709	112	26			NOUN
fcis-25709	112	27			PROPN
fcis-25709	112	28			NUM
fcis-25709	112	29			NUM
fcis-25709	112	30			NOUN
fcis-25709	112	31			PROPN
fcis-25709	112	32			PROPN
fcis-25709	112	33			NOUN
fcis-25709	112	34			NUM
fcis-25709	112	35			NUM
fcis-25709	112	36			NOUN
fcis-25709	112	37			NOUN
fcis-25709	112	38	(	(	PUNCT
fcis-25709	112	39	9	9	NUM
fcis-25709	112	40	)	)	PUNCT
fcis-25709	112	41	where	where	SCONJ
fcis-25709	112	42	iv	iv	NUM
fcis-25709	112	43	and	and	CCONJ
fcis-25709	112	44	ie	ie	ADV
fcis-25709	112	45	represent	represent	VERB
fcis-25709	112	46	the	the	DET
fcis-25709	112	47	node	node	ADJ
fcis-25709	112	48	feature	feature	NOUN
fcis-25709	112	49	set	set	VERB
fcis-25709	112	50	and	and	CCONJ
fcis-25709	112	51	edge	edge	NOUN
fcis-25709	112	52	feature	feature	NOUN
fcis-25709	112	53	set	set	VERB
fcis-25709	112	54	respectively	respectively	ADV
fcis-25709	112	55	in	in	ADP
fcis-25709	112	56	the	the	DET
fcis-25709	112	57	local	local	ADJ
fcis-25709	112	58	graph	graph	NOUN
fcis-25709	112	59	ig	ig	PROPN
fcis-25709	112	60	,	,	PUNCT
fcis-25709	112	61	ij	ij	INTJ
fcis-25709	112	62	if	if	SCONJ
fcis-25709	112	63	f	f	PROPN
fcis-25709	112	64	represents	represent	VERB
fcis-25709	112	65	the	the	DET
fcis-25709	112	66	relationship	relationship	NOUN
fcis-25709	112	67	feature	feature	NOUN
fcis-25709	112	68	between	between	ADP
fcis-25709	112	69	two	two	NUM
fcis-25709	112	70	points	point	NOUN
fcis-25709	112	71	,	,	PUNCT
fcis-25709	112	72			NOUN
fcis-25709	112	73	g	g	NOUN
fcis-25709	113	1			PROPN
fcis-25709	113	2	is	be	AUX
fcis-25709	113	3	a	a	DET
fcis-25709	113	4	nonlinear	nonlinear	ADJ
fcis-25709	113	5	function,	function,	NOUN
fcis-25709	113	6	is	be	AUX
fcis-25709	113	7	a	a	DET
fcis-25709	113	8	learnable	learnable	ADJ
fcis-25709	113	9	parameter	parameter	NOUN
fcis-25709	113	10	,	,	PUNCT
fcis-25709	113	11	ije	ije	PROPN
fcis-25709	113	12	is	be	AUX
fcis-25709	113	13	the	the	DET
fcis-25709	113	14	directed	direct	VERB
fcis-25709	113	15	feature	feature	NOUN
fcis-25709	113	16	distance	distance	NOUN
fcis-25709	113	17	between	between	ADP
fcis-25709	113	18	the	the	DET
fcis-25709	113	19	reference	reference	NOUN
fcis-25709	113	20	center	center	NOUN
fcis-25709	113	21	point	point	NOUN
fcis-25709	113	22	ip	ip	NOUN
fcis-25709	113	23	and	and	CCONJ
fcis-25709	113	24	its	its	PRON
fcis-25709	113	25	jth	jth	PROPN
fcis-25709	113	26	adjacent	adjacent	ADJ
fcis-25709	113	27	point	point	NOUN
fcis-25709	113	28	feature	feature	NOUN
fcis-25709	113	29	ijf	ijf	NOUN
fcis-25709	113	30	calculated	calculate	VERB
fcis-25709	113	31	by	by	ADP
fcis-25709	113	32	using	use	VERB
fcis-25709	113	33	the	the	DET
fcis-25709	113	34	euclidean	euclidean	ADJ
fcis-25709	113	35	distance	distance	NOUN
fcis-25709	113	36	as	as	ADP
fcis-25709	113	37	the	the	DET
fcis-25709	113	38	edge	edge	NOUN
fcis-25709	113	39	feature	feature	NOUN
fcis-25709	113	40	.	.	PUNCT
fcis-25709	114	1	thirdly	thirdly	ADV
fcis-25709	114	2	,	,	PUNCT
fcis-25709	114	3	the	the	DET
fcis-25709	114	4	relative	relative	ADJ
fcis-25709	114	5	position	position	NOUN
fcis-25709	114	6	coding	code	VERB
fcis-25709	114	7	(	(	PUNCT
fcis-25709	114	8	rpc	rpc	NOUN
fcis-25709	114	9	)	)	PUNCT
fcis-25709	114	10	followed	follow	VERB
fcis-25709	114	11	by	by	ADP
fcis-25709	114	12	the	the	DET
fcis-25709	114	13	shared	share	VERB
fcis-25709	114	14	multi	multi	ADJ
fcis-25709	114	15	-	-	ADJ
fcis-25709	114	16	layer	layer	ADJ
fcis-25709	114	17	perceptron	perceptron	NOUN
fcis-25709	114	18	is	be	AUX
fcis-25709	114	19	introduced	introduce	VERB
fcis-25709	114	20	,	,	PUNCT
fcis-25709	114	21	the	the	DET
fcis-25709	114	22	local	local	ADJ
fcis-25709	114	23	relative	relative	ADJ
fcis-25709	114	24	feature	feature	NOUN
fcis-25709	114	25	r	r	NOUN
fcis-25709	114	26	ijl	ijl	NOUN
fcis-25709	114	27	of	of	ADP
fcis-25709	114	28	the	the	DET
fcis-25709	114	29	reference	reference	NOUN
fcis-25709	114	30	central	central	ADJ
fcis-25709	114	31	point	point	NOUN
fcis-25709	114	32	ip	ip	NOUN
fcis-25709	114	33	is	be	AUX
fcis-25709	114	34	obtained	obtain	VERB
fcis-25709	114	35	through	through	ADP
fcis-25709	114	36	the	the	DET
fcis-25709	114	37	position	position	NOUN
fcis-25709	114	38	information	information	NOUN
fcis-25709	114	39	of	of	ADP
fcis-25709	114	40	its	its	PRON
fcis-25709	114	41	adjacent	adjacent	ADJ
fcis-25709	114	42	point	point	NOUN
fcis-25709	114	43	ijp	ijp	ADV
fcis-25709	114	44	,	,	PUNCT
fcis-25709	114	45	which	which	PRON
fcis-25709	114	46	can	can	AUX
fcis-25709	114	47	be	be	AUX
fcis-25709	114	48	represented	represent	VERB
fcis-25709	114	49	as	as	SCONJ
fcis-25709	114	50	follows	follow	VERB
fcis-25709	114	51	:	:	PUNCT
fcis-25709	114	52			PROPN
fcis-25709	114	53			PROPN
fcis-25709	114	54			PROPN
fcis-25709	114	55	,	,	PUNCT
fcis-25709	114	56	,	,	PUNCT
fcis-25709	114	57	,	,	PUNCT
fcis-25709	115	1	r	r	NOUN
fcis-25709	115	2	ij	ij	INTJ
fcis-25709	116	1	i	i	PRON
fcis-25709	116	2	j	j	INTJ
fcis-25709	117	1	ij	ij	INTJ
fcis-25709	118	1	i	i	INTJ
fcis-25709	118	2	ij	ij	INTJ
fcis-25709	118	3	il	il	PROPN
fcis-25709	118	4	mlp	mlp	PROPN
fcis-25709	118	5	p	p	PROPN
fcis-25709	119	1	p	p	PROPN
fcis-25709	119	2	p	p	X
fcis-25709	119	3	p	p	X
fcis-25709	119	4	p	p	NOUN
fcis-25709	119	5	p	p	NOUN
fcis-25709	119	6			PROPN
fcis-25709	119	7			NOUN
fcis-25709	119	8			NOUN
fcis-25709	119	9			PROPN
fcis-25709	119	10	(	(	PUNCT
fcis-25709	119	11	10	10	NUM
fcis-25709	119	12	)	)	PUNCT
fcis-25709	119	13	where	where	SCONJ
fcis-25709	119	14	ip	ip	NOUN
fcis-25709	119	15	and	and	CCONJ
fcis-25709	119	16	ijp	ijp	NOUN
fcis-25709	119	17	are	be	AUX
fcis-25709	119	18	coordinate	coordinate	ADJ
fcis-25709	119	19	points	point	NOUN
fcis-25709	119	20	with	with	ADP
fcis-25709	119	21	xyz	xyz	NOUN
fcis-25709	119	22	feature	feature	NOUN
fcis-25709	119	23	channels	channel	NOUN
fcis-25709	120	1	,	,	PUNCT
fcis-25709	120	2			PROPN
fcis-25709	120	3	is	be	AUX
fcis-25709	120	4	the	the	DET
fcis-25709	120	5	calculation	calculation	NOUN
fcis-25709	120	6	of	of	ADP
fcis-25709	120	7	euclidean	euclidean	ADJ
fcis-25709	120	8	distance	distance	NOUN
fcis-25709	120	9	,	,	PUNCT
fcis-25709	120	10	and	and	CCONJ
fcis-25709	120	11			PROPN
fcis-25709	120	12			PROPN
fcis-25709	120	13	,	,	PUNCT
fcis-25709	120	14	is	be	AUX
fcis-25709	120	15	the	the	DET
fcis-25709	120	16	feature	feature	NOUN
fcis-25709	120	17	concatenation	concatenation	NOUN
fcis-25709	120	18	.	.	PUNCT
fcis-25709	121	1	then	then	ADV
fcis-25709	121	2	,	,	PUNCT
fcis-25709	121	3	the	the	DET
fcis-25709	121	4	edge	edge	NOUN
fcis-25709	121	5	feature	feature	NOUN
fcis-25709	121	6	ije	ije	NOUN
fcis-25709	121	7	of	of	ADP
fcis-25709	121	8	each	each	DET
fcis-25709	121	9	reference	reference	NOUN
fcis-25709	121	10	central	central	ADJ
fcis-25709	121	11	point	point	NOUN
fcis-25709	121	12	ip	ip	NOUN
fcis-25709	121	13	and	and	CCONJ
fcis-25709	121	14	the	the	DET
fcis-25709	121	15	corresponding	corresponding	ADJ
fcis-25709	121	16	local	local	ADJ
fcis-25709	121	17	relative	relative	ADJ
fcis-25709	121	18	feature	feature	NOUN
fcis-25709	121	19	r	r	PROPN
fcis-25709	121	20	ijs	ijs	PROPN
fcis-25709	121	21	are	be	AUX
fcis-25709	121	22	combined	combine	VERB
fcis-25709	121	23	to	to	PART
fcis-25709	121	24	obtain	obtain	VERB
fcis-25709	121	25	the	the	DET
fcis-25709	121	26	enhanced	enhance	VERB
fcis-25709	121	27	edge	edge	NOUN
fcis-25709	121	28	feature	feature	NOUN
fcis-25709	121	29	ije	ije	PROPN
fcis-25709	121	30	,	,	PUNCT
fcis-25709	121	31	as	as	SCONJ
fcis-25709	121	32	shown	show	VERB
fcis-25709	121	33	in	in	ADP
fcis-25709	121	34	formula	formula	NOUN
fcis-25709	121	35	(	(	PUNCT
fcis-25709	121	36	11	11	NUM
fcis-25709	121	37	)	)	PUNCT
fcis-25709	121	38	:	:	PUNCT
fcis-25709	121	39	,	,	PUNCT
fcis-25709	121	40	rij	rij	X
fcis-25709	121	41	ij	ij	NOUN
fcis-25709	121	42	ije	ije	PROPN
fcis-25709	121	43	e	e	PROPN
fcis-25709	121	44	l	l	X
fcis-25709	121	45			PROPN
fcis-25709	121	46			VERB
fcis-25709	121	47			PROPN
fcis-25709	121	48			PROPN
fcis-25709	121	49	(	(	PUNCT
fcis-25709	121	50	11	11	NUM
fcis-25709	121	51	)	)	PUNCT
fcis-25709	121	52	in	in	ADP
fcis-25709	121	53	order	order	NOUN
fcis-25709	121	54	to	to	PART
fcis-25709	121	55	make	make	VERB
fcis-25709	121	56	more	more	ADV
fcis-25709	121	57	effective	effective	ADJ
fcis-25709	121	58	use	use	NOUN
fcis-25709	121	59	of	of	ADP
fcis-25709	121	60	the	the	DET
fcis-25709	121	61	most	most	ADV
fcis-25709	121	62	critical	critical	ADJ
fcis-25709	121	63	information	information	NOUN
fcis-25709	121	64	in	in	ADP
fcis-25709	121	65	each	each	DET
fcis-25709	121	66	enhanced	enhance	VERB
fcis-25709	121	67	edge	edge	NOUN
fcis-25709	121	68	feature	feature	NOUN
fcis-25709	121	69	,	,	PUNCT
fcis-25709	121	70	the	the	DET
fcis-25709	121	71	attention	attention	NOUN
fcis-25709	121	72	pooling	pool	VERB
fcis-25709	121	73	to	to	AUX
fcis-25709	121	74	graph	graph	VERB
fcis-25709	121	75	pooling	pool	VERB
fcis-25709	121	76	strategy	strategy	NOUN
fcis-25709	121	77	based	base	VERB
fcis-25709	121	78	on	on	ADP
fcis-25709	121	79	self	self	NOUN
fcis-25709	121	80	-	-	PUNCT
fcis-25709	121	81	attention	attention	NOUN
fcis-25709	121	82	mechanism	mechanism	NOUN
fcis-25709	121	83	is	be	AUX
fcis-25709	121	84	used	use	VERB
fcis-25709	121	85	to	to	PART
fcis-25709	121	86	aggregate	aggregate	VERB
fcis-25709	121	87	features	feature	NOUN
fcis-25709	121	88	.	.	PUNCT
fcis-25709	122	1	each	each	DET
fcis-25709	122	2	enhanced	enhance	VERB
fcis-25709	122	3	edge	edge	NOUN
fcis-25709	122	4	feature	feature	NOUN
fcis-25709	122	5	ije	ije	PROPN
fcis-25709	122	6	of	of	ADP
fcis-25709	122	7	reference	reference	NOUN
fcis-25709	122	8	center	center	NOUN
fcis-25709	122	9	point	point	NOUN
fcis-25709	122	10	ip	ip	NOUN
fcis-25709	122	11	is	be	AUX
fcis-25709	122	12	aggregated	aggregate	VERB
fcis-25709	122	13	to	to	PART
fcis-25709	122	14	extract	extract	VERB
fcis-25709	122	15	local	local	ADJ
fcis-25709	122	16	geometric	geometric	ADJ
fcis-25709	122	17	features	feature	NOUN
fcis-25709	122	18	with	with	ADP
fcis-25709	122	19	high	high	ADJ
fcis-25709	122	20	discriminating	discriminate	VERB
fcis-25709	122	21	power	power	NOUN
fcis-25709	122	22	.	.	PUNCT
fcis-25709	123	1	for	for	ADP
fcis-25709	123	2	the	the	DET
fcis-25709	123	3	resulting	result	VERB
fcis-25709	123	4	set	set	NOUN
fcis-25709	123	5	of	of	ADP
fcis-25709	123	6	enhanced	enhanced	ADJ
fcis-25709	123	7	edge	edge	NOUN
fcis-25709	123	8	features	feature	NOUN
fcis-25709	123	9			VERB
fcis-25709	123	10			X
fcis-25709	123	11	1	1	NOUN
fcis-25709	123	12	2	2	NUM
fcis-25709	123	13	,	,	PUNCT
fcis-25709	123	14	,	,	PUNCT
fcis-25709	123	15	,	,	PUNCT
fcis-25709	123	16	ij	ij	INTJ
fcis-25709	124	1	i	i	PRON
fcis-25709	125	1	i	i	PRON
fcis-25709	125	2	ije	ije	NOUN
fcis-25709	125	3	e	e	PROPN
fcis-25709	125	4	e	e	PROPN
fcis-25709	125	5	e	e	PROPN
fcis-25709	125	6			PROPN
fcis-25709	125	7			PROPN
fcis-25709	125	8			NOUN
fcis-25709	125	9	,	,	PUNCT
fcis-25709	125	10	an	an	DET
fcis-25709	125	11	attention	attention	NOUN
fcis-25709	125	12	coefficient	coefficient	NOUN
fcis-25709	125	13	ij	ij	NOUN
fcis-25709	125	14	is	be	AUX
fcis-25709	125	15	learned	learn	VERB
fcis-25709	125	16	for	for	ADP
fcis-25709	125	17	each	each	DET
fcis-25709	125	18	enhanced	enhance	VERB
fcis-25709	125	19	edge	edge	NOUN
fcis-25709	125	20	feature	feature	NOUN
fcis-25709	125	21	using	use	VERB
fcis-25709	125	22	the	the	DET
fcis-25709	125	23	shared	share	VERB
fcis-25709	125	24	activation	activation	NOUN
fcis-25709	125	25	function	function	NOUN
fcis-25709	125	26			NOUN
fcis-25709	125	27			VERB
fcis-25709	125	28			NUM
fcis-25709	125	29	and	and	CCONJ
fcis-25709	125	30	maxsoft	maxsoft	ADJ
fcis-25709	125	31	classifier	classifier	NOUN
fcis-25709	125	32	.	.	PUNCT
fcis-25709	126	1	the	the	DET
fcis-25709	126	2	aggregation	aggregation	NOUN
fcis-25709	126	3	process	process	NOUN
fcis-25709	126	4	is	be	AUX
fcis-25709	126	5	shown	show	VERB
fcis-25709	126	6	in	in	ADP
fcis-25709	126	7	formula	formula	NOUN
fcis-25709	126	8	(	(	PUNCT
fcis-25709	126	9	12	12	NUM
fcis-25709	126	10	):	):	PUNCT
fcis-25709	126	11			PROPN
fcis-25709	126	12			NOUN
fcis-25709	127	1			PROPN
fcis-25709	127	2			PROPN
fcis-25709	127	3			NOUN
fcis-25709	127	4	1	1	PROPN
fcis-25709	127	5	exp	exp	PROPN
fcis-25709	127	6	,	,	PUNCT
fcis-25709	127	7	max	max	PROPN
fcis-25709	127	8	exp	exp	NOUN
fcis-25709	127	9	,	,	PUNCT
fcis-25709	127	10	ij	ij	INTJ
fcis-25709	127	11	ij	ij	INTJ
fcis-25709	127	12	k	k	PROPN
fcis-25709	127	13	ijj	ijj	PROPN
fcis-25709	127	14	e	e	PROPN
fcis-25709	127	15	a	a	DET
fcis-25709	127	16	soft	soft	ADJ
fcis-25709	127	17	e	e	NOUN
fcis-25709	127	18	a	a	DET
fcis-25709	127	19			PROPN
fcis-25709	127	20			NOUN
fcis-25709	127	21			PROPN
fcis-25709	127	22			PROPN
fcis-25709	127	23			NOUN
fcis-25709	127	24			PROPN
fcis-25709	127	25			PROPN
fcis-25709	127	26			NOUN
fcis-25709	127	27			PROPN
fcis-25709	128	1			PROPN
fcis-25709	129	1			PROPN
fcis-25709	129	2			PROPN
fcis-25709	130	1			PROPN
fcis-25709	130	2			PROPN
fcis-25709	130	3			PROPN
fcis-25709	130	4			NUM
fcis-25709	130	5	(	(	PUNCT
fcis-25709	130	6	12	12	NUM
fcis-25709	130	7	)	)	PUNCT
fcis-25709	130	8	where	where	SCONJ
fcis-25709	130	9	1	1	NUM
fcis-25709	130	10	da	da	NOUN
fcis-25709	130	11	r	r	NOUN
fcis-25709	130	12			NOUN
fcis-25709	130	13	is	be	AUX
fcis-25709	130	14	the	the	DET
fcis-25709	130	15	learnable	learnable	ADJ
fcis-25709	130	16	attention	attention	NOUN
fcis-25709	130	17	coefficient	coefficient	NOUN
fcis-25709	130	18	matrix	matrix	NOUN
fcis-25709	130	19	.	.	PUNCT
fcis-25709	131	1	finally	finally	ADV
fcis-25709	131	2	,	,	PUNCT
fcis-25709	131	3	each	each	DET
fcis-25709	131	4	enhanced	enhance	VERB
fcis-25709	131	5	edge	edge	NOUN
fcis-25709	131	6	feature	feature	NOUN
fcis-25709	131	7	ije	ije	PROPN
fcis-25709	131	8	is	be	AUX
fcis-25709	131	9	multiplied	multiply	VERB
fcis-25709	131	10	and	and	CCONJ
fcis-25709	131	11	weighted	weight	VERB
fcis-25709	131	12	with	with	ADP
fcis-25709	131	13	the	the	DET
fcis-25709	131	14	corresponding	corresponding	ADJ
fcis-25709	131	15	learned	learn	VERB
fcis-25709	131	16	attention	attention	NOUN
fcis-25709	131	17	coefficient	coefficient	NOUN
fcis-25709	131	18	ij	ij	ADV
fcis-25709	131	19	,	,	PUNCT
fcis-25709	131	20	and	and	CCONJ
fcis-25709	131	21	the	the	DET
fcis-25709	131	22	central	central	ADJ
fcis-25709	131	23	point	point	NOUN
fcis-25709	131	24	feature	feature	NOUN
fcis-25709	131	25	is	be	AUX
fcis-25709	131	26	updated	update	VERB
fcis-25709	131	27	as	as	SCONJ
fcis-25709	131	28	shown	show	VERB
fcis-25709	131	29	in	in	ADP
fcis-25709	131	30	formula	formula	NOUN
fcis-25709	131	31	(	(	PUNCT
fcis-25709	131	32	13	13	NUM
fcis-25709	131	33	):	):	PUNCT
fcis-25709	131	34			NOUN
fcis-25709	131	35			PROPN
fcis-25709	131	36	1	1	NUM
fcis-25709	132	1	k	k	NOUN
fcis-25709	132	2	p	p	PROPN
fcis-25709	132	3	iji	iji	PROPN
fcis-25709	132	4	ij	ij	INTJ
fcis-25709	132	5	j	j	PROPN
fcis-25709	132	6	f	f	PROPN
fcis-25709	132	7	e	e	PROPN
fcis-25709	132	8			X
fcis-25709	132	9			PROPN
fcis-25709	132	10			PROPN
fcis-25709	132	11			X
fcis-25709	132	12			NUM
fcis-25709	132	13	(	(	PUNCT
fcis-25709	132	14	13	13	NUM
fcis-25709	132	15	)	)	PUNCT
fcis-25709	132	16	where	where	SCONJ
fcis-25709	132	17	p	p	NOUN
fcis-25709	132	18	if	if	SCONJ
fcis-25709	132	19	is	be	AUX
fcis-25709	132	20	the	the	DET
fcis-25709	132	21	aggregation	aggregation	NOUN
fcis-25709	132	22	feature	feature	NOUN
fcis-25709	132	23	of	of	ADP
fcis-25709	132	24	the	the	DET
fcis-25709	132	25	reference	reference	NOUN
fcis-25709	132	26	central	central	ADJ
fcis-25709	132	27	point	point	NOUN
fcis-25709	132	28	ip	ip	NOUN
fcis-25709	132	29	in	in	ADP
fcis-25709	132	30	the	the	DET
fcis-25709	132	31	local	local	ADJ
fcis-25709	132	32	graph	graph	NOUN
fcis-25709	132	33	,	,	PUNCT
fcis-25709	132	34	and	and	CCONJ
fcis-25709	132	35			PROPN
fcis-25709	132	36	is	be	AUX
fcis-25709	132	37	the	the	DET
fcis-25709	132	38	dot	dot	NOUN
fcis-25709	132	39	product	product	NOUN
fcis-25709	132	40	operator	operator	NOUN
fcis-25709	132	41	.	.	PUNCT
fcis-25709	133	1	reference	reference	NOUN
fcis-25709	133	2	resnet	resnet	VERB
fcis-25709	133	3	[	[	X
fcis-25709	133	4	21	21	NUM
fcis-25709	133	5	]	]	X
fcis-25709	133	6	residual	residual	ADJ
fcis-25709	133	7	module	module	NOUN
fcis-25709	133	8	design	design	NOUN
fcis-25709	133	9	,	,	PUNCT
fcis-25709	133	10	fgco	fgco	PROPN
fcis-25709	133	11	chose	choose	VERB
fcis-25709	133	12	to	to	PART
fcis-25709	133	13	enhance	enhance	VERB
fcis-25709	133	14	the	the	DET
fcis-25709	133	15	perceptual	perceptual	ADJ
fcis-25709	133	16	range	range	NOUN
fcis-25709	133	17	of	of	ADP
fcis-25709	133	18	each	each	DET
fcis-25709	133	19	point	point	NOUN
fcis-25709	133	20	to	to	PART
fcis-25709	133	21	capture	capture	VERB
fcis-25709	133	22	the	the	DET
fcis-25709	133	23	features	feature	NOUN
fcis-25709	133	24	of	of	ADP
fcis-25709	133	25	neighboring	neighboring	NOUN
fcis-25709	133	26	points	point	NOUN
fcis-25709	133	27	by	by	ADP
fcis-25709	133	28	connecting	connect	VERB
fcis-25709	133	29	and	and	CCONJ
fcis-25709	133	30	stacking	stack	VERB
fcis-25709	133	31	two	two	NUM
fcis-25709	133	32	fgco	fgco	NOUN
fcis-25709	133	33	and	and	CCONJ
fcis-25709	133	34	apl	apl	NOUN
fcis-25709	133	35	with	with	ADP
fcis-25709	133	36	dense	dense	ADJ
fcis-25709	133	37	jumps	jump	NOUN
fcis-25709	133	38	.	.	PUNCT
fcis-25709	134	1	in	in	ADP
fcis-25709	134	2	order	order	NOUN
fcis-25709	134	3	to	to	PART
fcis-25709	134	4	fully	fully	ADV
fcis-25709	134	5	demonstrate	demonstrate	VERB
fcis-25709	134	6	the	the	DET
fcis-25709	134	7	performance	performance	NOUN
fcis-25709	134	8	of	of	ADP
fcis-25709	134	9	the	the	DET
fcis-25709	134	10	feature	feature	NOUN
fcis-25709	134	11	aggregation	aggregation	NOUN
fcis-25709	134	12	unit	unit	NOUN
fcis-25709	134	13	,	,	PUNCT
fcis-25709	134	14	the	the	DET
fcis-25709	134	15	local	local	ADJ
fcis-25709	134	16	feature	feature	NOUN
fcis-25709	134	17	extraction	extraction	NOUN
fcis-25709	134	18	capability	capability	NOUN
fcis-25709	134	19	in	in	ADP
fcis-25709	134	20	the	the	DET
fcis-25709	134	21	point	point	NOUN
fcis-25709	134	22	cloud	cloud	NOUN
fcis-25709	134	23	is	be	AUX
fcis-25709	134	24	visualized	visualize	VERB
fcis-25709	134	25	.	.	PUNCT
fcis-25709	135	1	as	as	SCONJ
fcis-25709	135	2	shown	show	VERB
fcis-25709	135	3	in	in	ADP
fcis-25709	135	4	figure	figure	NOUN
fcis-25709	135	5	5	5	NUM
fcis-25709	135	6	,	,	PUNCT
fcis-25709	135	7	the	the	DET
fcis-25709	135	8	knn	knn	PROPN
fcis-25709	135	9	search	search	NOUN
fcis-25709	135	10	range	range	NOUN
fcis-25709	135	11	is	be	AUX
fcis-25709	135	12	set	set	VERB
fcis-25709	135	13	to	to	ADP
fcis-25709	135	14	5	5	NUM
fcis-25709	135	15	in	in	ADP
fcis-25709	135	16	this	this	DET
fcis-25709	135	17	paper	paper	NOUN
fcis-25709	135	18	,	,	PUNCT
fcis-25709	135	19	with	with	ADP
fcis-25709	135	20	red	red	ADJ
fcis-25709	135	21	dots	dot	NOUN
fcis-25709	135	22	representing	represent	VERB
fcis-25709	135	23	the	the	DET
fcis-25709	135	24	central	central	ADJ
fcis-25709	135	25	point	point	NOUN
fcis-25709	135	26	,	,	PUNCT
fcis-25709	135	27	purple	purple	ADJ
fcis-25709	135	28	dots	dot	NOUN
fcis-25709	135	29	representing	represent	VERB
fcis-25709	135	30	the	the	DET
fcis-25709	135	31	nearest	near	ADJ
fcis-25709	135	32	neighbors	neighbor	NOUN
fcis-25709	135	33	of	of	ADP
fcis-25709	135	34	the	the	DET
fcis-25709	135	35	central	central	ADJ
fcis-25709	135	36	point	point	NOUN
fcis-25709	135	37	,	,	PUNCT
fcis-25709	135	38	dotted	dot	VERB
fcis-25709	135	39	arrows	arrow	NOUN
fcis-25709	135	40	representing	represent	VERB
fcis-25709	135	41	the	the	DET
fcis-25709	135	42	flow	flow	NOUN
fcis-25709	135	43	direction	direction	NOUN
fcis-25709	135	44	of	of	ADP
fcis-25709	135	45	information	information	NOUN
fcis-25709	135	46	aggregation	aggregation	NOUN
fcis-25709	135	47	,	,	PUNCT
fcis-25709	135	48	and	and	CCONJ
fcis-25709	135	49	dotted	dotted	ADJ
fcis-25709	135	50	circles	circle	NOUN
fcis-25709	135	51	representing	represent	VERB
fcis-25709	135	52	the	the	DET
fcis-25709	135	53	range	range	NOUN
fcis-25709	135	54	of	of	ADP
fcis-25709	135	55	receptive	receptive	ADJ
fcis-25709	135	56	fields	field	NOUN
fcis-25709	135	57	of	of	ADP
fcis-25709	135	58	the	the	DET
fcis-25709	135	59	central	central	ADJ
fcis-25709	135	60	point	point	NOUN
fcis-25709	135	61	.	.	PUNCT
fcis-25709	136	1	in	in	ADP
fcis-25709	136	2	the	the	DET
fcis-25709	136	3	first	first	ADJ
fcis-25709	136	4	stage	stage	NOUN
fcis-25709	136	5	,	,	PUNCT
fcis-25709	136	6	shallow	shallow	ADJ
fcis-25709	136	7	local	local	ADJ
fcis-25709	136	8	features	feature	NOUN
fcis-25709	136	9	are	be	AUX
fcis-25709	136	10	captured	capture	VERB
fcis-25709	136	11	,	,	PUNCT
fcis-25709	136	12	and	and	CCONJ
fcis-25709	136	13	after	after	ADP
fcis-25709	136	14	information	information	NOUN
fcis-25709	136	15	flow	flow	NOUN
fcis-25709	136	16	,	,	PUNCT
fcis-25709	136	17	the	the	DET
fcis-25709	136	18	information	information	NOUN
fcis-25709	136	19	receptive	receptive	ADJ
fcis-25709	136	20	field	field	NOUN
fcis-25709	136	21	of	of	ADP
fcis-25709	136	22	the	the	DET
fcis-25709	136	23	central	central	ADJ
fcis-25709	136	24	point	point	NOUN
fcis-25709	136	25	is	be	AUX
fcis-25709	136	26	further	far	ADV
fcis-25709	136	27	expanded	expand	VERB
fcis-25709	136	28	in	in	ADP
fcis-25709	136	29	the	the	DET
fcis-25709	136	30	second	second	ADJ
fcis-25709	136	31	stage	stage	NOUN
fcis-25709	136	32	,	,	PUNCT
fcis-25709	136	33	and	and	CCONJ
fcis-25709	136	34	the	the	DET
fcis-25709	136	35	context	context	NOUN
fcis-25709	136	36	information	information	NOUN
fcis-25709	136	37	in	in	ADP
fcis-25709	136	38	a	a	DET
fcis-25709	136	39	larger	large	ADJ
fcis-25709	136	40	area	area	NOUN
fcis-25709	136	41	is	be	AUX
fcis-25709	136	42	extracted	extract	VERB
fcis-25709	136	43	by	by	ADP
fcis-25709	136	44	using	use	VERB
fcis-25709	136	45	the	the	DET
fcis-25709	136	46	feature	feature	NOUN
fcis-25709	136	47	maps	map	NOUN
fcis-25709	136	48	accumulated	accumulate	VERB
fcis-25709	136	49	in	in	ADP
fcis-25709	136	50	the	the	DET
fcis-25709	136	51	previous	previous	ADJ
fcis-25709	136	52	stage	stage	NOUN
fcis-25709	136	53	.	.	PUNCT
fcis-25709	137	1	by	by	ADP
fcis-25709	137	2	expanding	expand	VERB
fcis-25709	137	3	the	the	DET
fcis-25709	137	4	sensing	sense	VERB
fcis-25709	137	5	domain	domain	NOUN
fcis-25709	137	6	,	,	PUNCT
fcis-25709	137	7	mffm	mffm	NOUN
fcis-25709	137	8	promotes	promote	VERB
fcis-25709	137	9	feature	feature	NOUN
fcis-25709	137	10	propagation	propagation	NOUN
fcis-25709	137	11	,	,	PUNCT
fcis-25709	137	12	ensures	ensure	VERB
fcis-25709	137	13	computational	computational	ADJ
fcis-25709	137	14	efficiency	efficiency	NOUN
fcis-25709	137	15	,	,	PUNCT
fcis-25709	137	16	and	and	CCONJ
fcis-25709	137	17	enhances	enhance	VERB
fcis-25709	137	18	the	the	DET
fcis-25709	137	19	ability	ability	NOUN
fcis-25709	137	20	of	of	ADP
fcis-25709	137	21	the	the	DET
fcis-25709	137	22	network	network	NOUN
fcis-25709	137	23	to	to	PART
fcis-25709	137	24	capture	capture	VERB
fcis-25709	137	25	local	local	ADJ
fcis-25709	137	26	features	feature	NOUN
fcis-25709	137	27	of	of	ADP
fcis-25709	137	28	point	point	NOUN
fcis-25709	137	29	cloud	cloud	NOUN
fcis-25709	137	30	data	datum	NOUN
fcis-25709	137	31	,	,	PUNCT
fcis-25709	137	32	thus	thus	ADV
fcis-25709	137	33	improving	improve	VERB
fcis-25709	137	34	the	the	DET
fcis-25709	137	35	depth	depth	NOUN
fcis-25709	137	36	extraction	extraction	NOUN
fcis-25709	137	37	ability	ability	NOUN
fcis-25709	137	38	of	of	ADP
fcis-25709	137	39	the	the	DET
fcis-25709	137	40	network	network	NOUN
fcis-25709	137	41	for	for	ADP
fcis-25709	137	42	multi	multi	ADJ
fcis-25709	137	43	-	-	ADJ
fcis-25709	137	44	scale	scale	ADJ
fcis-25709	137	45	features	feature	NOUN
fcis-25709	137	46	.	.	PUNCT
fcis-25709	138	1	15	15	NUM
fcis-25709	138	2	fig	fig	NOUN
fcis-25709	138	3	5	5	NUM
fcis-25709	138	4	.	.	PUNCT
fcis-25709	138	5	visualization	visualization	NOUN
fcis-25709	138	6	of	of	ADP
fcis-25709	138	7	local	local	ADJ
fcis-25709	138	8	feature	feature	NOUN
fcis-25709	138	9	extraction	extraction	NOUN
fcis-25709	138	10	capabilities	capability	NOUN
fcis-25709	138	11	2.3	2.3	NUM
fcis-25709	138	12	.	.	PUNCT
fcis-25709	139	1	cross	cross	ADJ
fcis-25709	139	2	-	-	ADJ
fcis-25709	139	3	layer	layer	ADJ
fcis-25709	139	4	multi	multi	ADJ
fcis-25709	139	5	-	-	ADJ
fcis-25709	139	6	loss	loss	ADJ
fcis-25709	139	7	monitoring	monitoring	NOUN
fcis-25709	139	8	module	module	NOUN
fcis-25709	139	9	the	the	DET
fcis-25709	139	10	dense	dense	ADJ
fcis-25709	139	11	nested	nested	ADJ
fcis-25709	139	12	network	network	NOUN
fcis-25709	139	13	architecture	architecture	NOUN
fcis-25709	139	14	proposed	propose	VERB
fcis-25709	139	15	in	in	ADP
fcis-25709	139	16	this	this	DET
fcis-25709	139	17	paper	paper	NOUN
fcis-25709	139	18	spans	span	VERB
fcis-25709	139	19	multiple	multiple	ADJ
fcis-25709	139	20	scales	scale	NOUN
fcis-25709	139	21	in	in	ADP
fcis-25709	139	22	feature	feature	NOUN
fcis-25709	139	23	fusion	fusion	NOUN
fcis-25709	139	24	,	,	PUNCT
fcis-25709	139	25	thus	thus	ADV
fcis-25709	139	26	increasing	increase	VERB
fcis-25709	139	27	the	the	DET
fcis-25709	139	28	complexity	complexity	NOUN
fcis-25709	139	29	of	of	ADP
fcis-25709	139	30	feature	feature	NOUN
fcis-25709	139	31	fusion	fusion	NOUN
fcis-25709	139	32	.	.	PUNCT
fcis-25709	140	1	however	however	ADV
fcis-25709	140	2	,	,	PUNCT
fcis-25709	140	3	this	this	DET
fcis-25709	140	4	complexity	complexity	NOUN
fcis-25709	140	5	also	also	ADV
fcis-25709	140	6	makes	make	VERB
fcis-25709	140	7	the	the	DET
fcis-25709	140	8	network	network	NOUN
fcis-25709	140	9	training	training	NOUN
fcis-25709	140	10	process	process	NOUN
fcis-25709	140	11	difficult	difficult	ADJ
fcis-25709	140	12	to	to	PART
fcis-25709	140	13	control	control	VERB
fcis-25709	140	14	.	.	PUNCT
fcis-25709	141	1	to	to	PART
fcis-25709	141	2	ensure	ensure	VERB
fcis-25709	141	3	effective	effective	ADJ
fcis-25709	141	4	training	training	NOUN
fcis-25709	141	5	,	,	PUNCT
fcis-25709	141	6	we	we	PRON
fcis-25709	141	7	need	need	VERB
fcis-25709	141	8	to	to	PART
fcis-25709	141	9	integrate	integrate	VERB
fcis-25709	141	10	features	feature	NOUN
fcis-25709	141	11	efficiently	efficiently	ADV
fcis-25709	141	12	.	.	PUNCT
fcis-25709	142	1	inspired	inspire	VERB
fcis-25709	142	2	by	by	ADP
fcis-25709	142	3	deep	deep	ADJ
fcis-25709	142	4	supervision	supervision	NOUN
fcis-25709	142	5	network[22	network[22	PROPN
fcis-25709	142	6	]	]	PUNCT
fcis-25709	142	7	and	and	CCONJ
fcis-25709	142	8	multi	multi	ADJ
fcis-25709	142	9	-	-	ADJ
fcis-25709	142	10	scale	scale	ADJ
fcis-25709	142	11	structure	structure	NOUN
fcis-25709	142	12	sensing	sense	VERB
fcis-25709	142	13	network[23	network[23	PROPN
fcis-25709	142	14	]	]	PUNCT
fcis-25709	142	15	,	,	PUNCT
fcis-25709	142	16	mdnn	mdnn	NOUN
fcis-25709	142	17	proposes	propose	VERB
fcis-25709	142	18	a	a	DET
fcis-25709	142	19	cross	cross	ADJ
fcis-25709	142	20	-	-	ADJ
fcis-25709	142	21	layer	layer	ADJ
fcis-25709	142	22	multi	multi	ADJ
fcis-25709	142	23	-	-	ADJ
fcis-25709	142	24	loss	loss	ADJ
fcis-25709	142	25	supervision	supervision	NOUN
fcis-25709	142	26	module	module	NOUN
fcis-25709	142	27	.	.	PUNCT
fcis-25709	143	1	the	the	DET
fcis-25709	143	2	module	module	NOUN
fcis-25709	143	3	can	can	AUX
fcis-25709	143	4	deeply	deeply	ADV
fcis-25709	143	5	optimize	optimize	VERB
fcis-25709	143	6	multiple	multiple	ADJ
fcis-25709	143	7	feature	feature	NOUN
fcis-25709	143	8	fusion	fusion	NOUN
fcis-25709	143	9	processes	process	NOUN
fcis-25709	143	10	across	across	ADP
fcis-25709	143	11	the	the	DET
fcis-25709	143	12	network	network	NOUN
fcis-25709	143	13	,	,	PUNCT
fcis-25709	143	14	improve	improve	VERB
fcis-25709	143	15	the	the	DET
fcis-25709	143	16	ability	ability	NOUN
fcis-25709	143	17	of	of	ADP
fcis-25709	143	18	network	network	NOUN
fcis-25709	143	19	training	training	NOUN
fcis-25709	143	20	control	control	NOUN
fcis-25709	143	21	and	and	CCONJ
fcis-25709	143	22	feature	feature	NOUN
fcis-25709	143	23	fusion	fusion	NOUN
fcis-25709	143	24	,	,	PUNCT
fcis-25709	143	25	and	and	CCONJ
fcis-25709	143	26	further	far	ADV
fcis-25709	143	27	adjust	adjust	VERB
fcis-25709	143	28	the	the	DET
fcis-25709	143	29	weight	weight	NOUN
fcis-25709	143	30	of	of	ADP
fcis-25709	143	31	categories	category	NOUN
fcis-25709	143	32	to	to	PART
fcis-25709	143	33	improve	improve	VERB
fcis-25709	143	34	the	the	DET
fcis-25709	143	35	stability	stability	NOUN
fcis-25709	143	36	of	of	ADP
fcis-25709	143	37	the	the	DET
fcis-25709	143	38	network	network	NOUN
fcis-25709	143	39	learning	learning	NOUN
fcis-25709	143	40	process	process	NOUN
fcis-25709	143	41	,	,	PUNCT
fcis-25709	143	42	thus	thus	ADV
fcis-25709	143	43	improving	improve	VERB
fcis-25709	143	44	the	the	DET
fcis-25709	143	45	segmentation	segmentation	NOUN
fcis-25709	143	46	accuracy	accuracy	NOUN
fcis-25709	143	47	of	of	ADP
fcis-25709	143	48	high	high	ADJ
fcis-25709	143	49	point	point	NOUN
fcis-25709	143	50	cloud	cloud	NOUN
fcis-25709	143	51	.	.	PUNCT
fcis-25709	144	1	as	as	SCONJ
fcis-25709	144	2	shown	show	VERB
fcis-25709	144	3	in	in	ADP
fcis-25709	144	4	figure	figure	NOUN
fcis-25709	144	5	6	6	NUM
fcis-25709	144	6	,	,	PUNCT
fcis-25709	144	7	the	the	DET
fcis-25709	144	8	module	module	NOUN
fcis-25709	144	9	adds	add	VERB
fcis-25709	144	10	sub	sub	NOUN
fcis-25709	144	11	-	-	NOUN
fcis-25709	144	12	loss	loss	NOUN
fcis-25709	144	13	at	at	ADP
fcis-25709	144	14	the	the	DET
fcis-25709	144	15	end	end	NOUN
fcis-25709	144	16	of	of	ADP
fcis-25709	144	17	each	each	DET
fcis-25709	144	18	decoder	decoder	NOUN
fcis-25709	144	19	,	,	PUNCT
fcis-25709	144	20	and	and	CCONJ
fcis-25709	144	21	through	through	ADP
fcis-25709	144	22	cross	cross	ADJ
fcis-25709	144	23	-	-	ADJ
fcis-25709	144	24	level	level	ADJ
fcis-25709	144	25	sub	sub	ADJ
fcis-25709	144	26	-	-	ADJ
fcis-25709	144	27	loss	loss	ADJ
fcis-25709	144	28	supervision	supervision	NOUN
fcis-25709	144	29	,	,	PUNCT
fcis-25709	144	30	sufficient	sufficient	ADJ
fcis-25709	144	31	feedback	feedback	NOUN
fcis-25709	144	32	can	can	AUX
fcis-25709	144	33	be	be	AUX
fcis-25709	144	34	obtained	obtain	VERB
fcis-25709	144	35	in	in	ADP
fcis-25709	144	36	the	the	DET
fcis-25709	144	37	training	training	NOUN
fcis-25709	144	38	process	process	NOUN
fcis-25709	144	39	of	of	ADP
fcis-25709	144	40	different	different	ADJ
fcis-25709	144	41	deep	deep	ADJ
fcis-25709	144	42	networks	network	NOUN
fcis-25709	144	43	,	,	PUNCT
fcis-25709	144	44	thus	thus	ADV
fcis-25709	144	45	realizing	realize	VERB
fcis-25709	144	46	the	the	DET
fcis-25709	144	47	training	training	NOUN
fcis-25709	144	48	control	control	NOUN
fcis-25709	144	49	of	of	ADP
fcis-25709	144	50	the	the	DET
fcis-25709	144	51	network	network	NOUN
fcis-25709	144	52	local	local	ADJ
fcis-25709	144	53	architecture	architecture	NOUN
fcis-25709	144	54	.	.	PUNCT
fcis-25709	145	1	each	each	DET
fcis-25709	145	2	subloss	subloss	NOUN
fcis-25709	145	3	consists	consist	VERB
fcis-25709	145	4	of	of	ADP
fcis-25709	145	5	a	a	DET
fcis-25709	145	6	1×1	1×1	NUM
fcis-25709	145	7	convolution	convolution	NOUN
fcis-25709	145	8	layer	layer	NOUN
fcis-25709	145	9	and	and	CCONJ
fcis-25709	145	10	a	a	DET
fcis-25709	145	11	weighted	weight	VERB
fcis-25709	145	12	cross	cross	NOUN
fcis-25709	145	13	entropy	entropy	PROPN
fcis-25709	145	14	loss	loss	PROPN
fcis-25709	145	15	function	function	NOUN
fcis-25709	145	16	wcel	wcel	NOUN
fcis-25709	145	17	,	,	PUNCT
fcis-25709	145	18	wcel	wcel	VERB
fcis-25709	145	19	advance	advance	NOUN
fcis-25709	145	20	along	along	ADP
fcis-25709	145	21	the	the	DET
fcis-25709	145	22	decoder	decoder	NOUN
fcis-25709	145	23	path	path	NOUN
fcis-25709	145	24	and	and	CCONJ
fcis-25709	145	25	dynamically	dynamically	ADV
fcis-25709	145	26	adjust	adjust	VERB
fcis-25709	145	27	the	the	DET
fcis-25709	145	28	weights	weight	NOUN
fcis-25709	145	29	based	base	VERB
fcis-25709	145	30	on	on	ADP
fcis-25709	145	31	the	the	DET
fcis-25709	145	32	points	point	NOUN
fcis-25709	145	33	in	in	ADP
fcis-25709	145	34	each	each	DET
fcis-25709	145	35	category	category	NOUN
fcis-25709	145	36	to	to	PART
fcis-25709	145	37	solve	solve	VERB
fcis-25709	145	38	the	the	DET
fcis-25709	145	39	class	class	NOUN
fcis-25709	145	40	imbalance	imbalance	NOUN
fcis-25709	145	41	problem	problem	NOUN
fcis-25709	145	42	and	and	CCONJ
fcis-25709	145	43	ensure	ensure	VERB
fcis-25709	145	44	the	the	DET
fcis-25709	145	45	effective	effective	ADJ
fcis-25709	145	46	fusion	fusion	NOUN
fcis-25709	145	47	and	and	CCONJ
fcis-25709	145	48	backpropagation	backpropagation	NOUN
fcis-25709	145	49	of	of	ADP
fcis-25709	145	50	multi	multi	ADJ
fcis-25709	145	51	-	-	ADJ
fcis-25709	145	52	scale	scale	ADJ
fcis-25709	145	53	supervision	supervision	NOUN
fcis-25709	145	54	information	information	NOUN
fcis-25709	145	55	.	.	PUNCT
fcis-25709	146	1	the	the	DET
fcis-25709	146	2	weighted	weighted	PROPN
fcis-25709	146	3	cross	cross	PROPN
fcis-25709	146	4	entropy	entropy	PROPN
fcis-25709	146	5	loss	loss	NOUN
fcis-25709	146	6	function	function	NOUN
fcis-25709	146	7	is	be	AUX
fcis-25709	146	8	shown	show	VERB
fcis-25709	146	9	in	in	ADP
fcis-25709	146	10	equation	equation	NOUN
fcis-25709	146	11	(	(	PUNCT
fcis-25709	146	12	14	14	NUM
fcis-25709	146	13	):	):	PUNCT
fcis-25709	146	14			PROPN
fcis-25709	146	15	(	(	PUNCT
fcis-25709	146	16	)	)	PUNCT
fcis-25709	146	17	log	log	NOUN
fcis-25709	146	18	(	(	PUNCT
fcis-25709	146	19	(	(	PUNCT
fcis-25709	146	20	)	)	PUNCT
fcis-25709	146	21	)	)	PUNCT
fcis-25709	146	22	pn	pn	PROPN
fcis-25709	146	23	wce	wce	PROPN
fcis-25709	147	1	i	i	PRON
fcis-25709	147	2	i	i	PRON
fcis-25709	147	3	ii	ii	VERB
fcis-25709	148	1	l	l	NOUN
fcis-25709	148	2	w	w	PROPN
fcis-25709	149	1	p	p	X
fcis-25709	149	2	y	y	PROPN
fcis-25709	149	3	p	p	NOUN
fcis-25709	149	4	y	y	NOUN
fcis-25709	149	5			PROPN
fcis-25709	149	6	(	(	PUNCT
fcis-25709	149	7	14	14	NUM
fcis-25709	149	8	)	)	PUNCT
fcis-25709	149	9	where	where	SCONJ
fcis-25709	149	10	pn	pn	PROPN
fcis-25709	149	11	represents	represent	VERB
fcis-25709	149	12	the	the	DET
fcis-25709	149	13	number	number	NOUN
fcis-25709	149	14	of	of	ADP
fcis-25709	149	15	total	total	ADJ
fcis-25709	149	16	sample	sample	NOUN
fcis-25709	149	17	points	point	NOUN
fcis-25709	149	18	,	,	PUNCT
fcis-25709	149	19			PROPN
fcis-25709	149	20	ip	ip	NOUN
fcis-25709	149	21	y	y	PROPN
fcis-25709	149	22	is	be	AUX
fcis-25709	149	23	the	the	DET
fcis-25709	149	24	true	true	ADJ
fcis-25709	149	25	distribution	distribution	NOUN
fcis-25709	149	26	value	value	NOUN
fcis-25709	149	27	of	of	ADP
fcis-25709	149	28	the	the	DET
fcis-25709	149	29	target	target	NOUN
fcis-25709	149	30	point	point	NOUN
fcis-25709	149	31	,	,	PUNCT
fcis-25709	149	32			PROPN
fcis-25709	149	33	ip	ip	NOUN
fcis-25709	149	34	y	y	PROPN
fcis-25709	149	35	is	be	AUX
fcis-25709	149	36	the	the	DET
fcis-25709	149	37	predicted	predict	VERB
fcis-25709	149	38	distribution	distribution	NOUN
fcis-25709	149	39	value	value	NOUN
fcis-25709	149	40	of	of	ADP
fcis-25709	149	41	the	the	DET
fcis-25709	149	42	target	target	NOUN
fcis-25709	149	43	point	point	NOUN
fcis-25709	149	44	,	,	PUNCT
fcis-25709	149	45	iw	iw	PROPN
fcis-25709	149	46	represents	represent	VERB
fcis-25709	149	47	the	the	DET
fcis-25709	149	48	weight	weight	NOUN
fcis-25709	149	49	coefficient	coefficient	NOUN
fcis-25709	149	50	of	of	ADP
fcis-25709	149	51	the	the	DET
fcis-25709	149	52	i	i	PROPN
fcis-25709	149	53	th	th	NOUN
fcis-25709	149	54	sample	sample	NOUN
fcis-25709	149	55	point	point	NOUN
fcis-25709	149	56	,	,	PUNCT
fcis-25709	149	57	which	which	PRON
fcis-25709	149	58	can	can	AUX
fcis-25709	149	59	be	be	AUX
fcis-25709	149	60	expressed	express	VERB
fcis-25709	149	61	as	as	ADP
fcis-25709	149	62	:	:	PUNCT
fcis-25709	149	63	13	13	NUM
fcis-25709	149	64	1	1	NUM
fcis-25709	149	65	,	,	PUNCT
fcis-25709	149	66	1	1	NUM
fcis-25709	149	67	,	,	PUNCT
fcis-25709	149	68	2,3	2,3	NUM
fcis-25709	149	69	,	,	PUNCT
fcis-25709	149	70	,	,	PUNCT
fcis-25709	149	71	13	13	NUM
fcis-25709	149	72	0.02	0.02	NUM
fcis-25709	149	73	nt	not	PART
fcis-25709	150	1	i	i	PRON
fcis-25709	150	2	n	n	CCONJ
fcis-25709	150	3	n	n	PROPN
fcis-25709	150	4	w	w	PROPN
fcis-25709	150	5	n	n	CCONJ
fcis-25709	150	6	n	n	CCONJ
fcis-25709	150	7			NUM
fcis-25709	150	8			NUM
fcis-25709	150	9			ADV
fcis-25709	150	10			X
fcis-25709	150	11			NOUN
fcis-25709	150	12	(	(	PUNCT
fcis-25709	150	13	15	15	NUM
fcis-25709	150	14	)	)	PUNCT
fcis-25709	150	15	where	where	SCONJ
fcis-25709	150	16	nn	nn	PROPN
fcis-25709	150	17	represents	represent	VERB
fcis-25709	150	18	the	the	DET
fcis-25709	150	19	number	number	NOUN
fcis-25709	150	20	of	of	ADP
fcis-25709	150	21	sample	sample	NOUN
fcis-25709	150	22	points	point	NOUN
fcis-25709	150	23	belonging	belong	VERB
fcis-25709	150	24	to	to	ADP
fcis-25709	150	25	the	the	DET
fcis-25709	150	26	n	n	PRON
fcis-25709	150	27	th	th	NOUN
fcis-25709	150	28	category	category	NOUN
fcis-25709	150	29	,	,	PUNCT
fcis-25709	150	30	and	and	CCONJ
fcis-25709	150	31	13	13	NUM
fcis-25709	150	32	represents	represent	VERB
fcis-25709	150	33	the	the	DET
fcis-25709	150	34	number	number	NOUN
fcis-25709	150	35	of	of	ADP
fcis-25709	150	36	categories	category	NOUN
fcis-25709	150	37	in	in	ADP
fcis-25709	150	38	the	the	DET
fcis-25709	150	39	s3dis	s3dis	PROPN
fcis-25709	150	40	dataset	dataset	NOUN
fcis-25709	150	41	.	.	PUNCT
fcis-25709	151	1	to	to	PART
fcis-25709	151	2	avoid	avoid	VERB
fcis-25709	151	3	the	the	DET
fcis-25709	151	4	situation	situation	NOUN
fcis-25709	151	5	where	where	SCONJ
fcis-25709	151	6	the	the	DET
fcis-25709	151	7	denominator	denominator	NOUN
fcis-25709	151	8	is	be	AUX
fcis-25709	151	9	zero	zero	NUM
fcis-25709	151	10	,	,	PUNCT
fcis-25709	151	11	add	add	VERB
fcis-25709	151	12	a	a	DET
fcis-25709	151	13	fraction	fraction	NOUN
fcis-25709	151	14	of	of	ADP
fcis-25709	151	15	0.02	0.02	NUM
fcis-25709	151	16	to	to	ADP
fcis-25709	151	17	the	the	DET
fcis-25709	151	18	denominator	denominator	NOUN
fcis-25709	151	19	.	.	PUNCT
fcis-25709	152	1	the	the	DET
fcis-25709	152	2	final	final	ADJ
fcis-25709	152	3	loss	loss	NOUN
fcis-25709	152	4	is	be	AUX
fcis-25709	152	5	calculated	calculate	VERB
fcis-25709	152	6	based	base	VERB
fcis-25709	152	7	on	on	ADP
fcis-25709	152	8	the	the	DET
fcis-25709	152	9	predicted	predict	VERB
fcis-25709	152	10	output	output	NOUN
fcis-25709	152	11	of	of	ADP
fcis-25709	152	12	each	each	DET
fcis-25709	152	13	sub	sub	NOUN
fcis-25709	152	14	-	-	NOUN
fcis-25709	152	15	loss	loss	NOUN
fcis-25709	152	16	,	,	PUNCT
fcis-25709	152	17	and	and	CCONJ
fcis-25709	152	18	the	the	DET
fcis-25709	152	19	entire	entire	ADJ
fcis-25709	152	20	network	network	NOUN
fcis-25709	152	21	uses	use	VERB
fcis-25709	152	22	the	the	DET
fcis-25709	152	23	multi	multi	ADJ
fcis-25709	152	24	-	-	ADJ
fcis-25709	152	25	scale	scale	ADJ
fcis-25709	152	26	loss	loss	NOUN
fcis-25709	152	27	function	function	NOUN
fcis-25709	152	28	ml	ml	NOUN
fcis-25709	152	29	to	to	PART
fcis-25709	152	30	precisely	precisely	ADV
fcis-25709	152	31	supervise	supervise	VERB
fcis-25709	152	32	the	the	DET
fcis-25709	152	33	training	training	NOUN
fcis-25709	152	34	.	.	PUNCT
fcis-25709	153	1	ml	ml	PROPN
fcis-25709	153	2	consists	consist	VERB
fcis-25709	153	3	of	of	ADP
fcis-25709	153	4	two	two	NUM
fcis-25709	153	5	parts	part	NOUN
fcis-25709	153	6	,	,	PUNCT
fcis-25709	153	7	namely	namely	ADV
fcis-25709	153	8	the	the	DET
fcis-25709	153	9	cross	cross	ADJ
fcis-25709	153	10	-	-	ADJ
fcis-25709	153	11	entropy	entropy	ADJ
fcis-25709	153	12	loss	loss	NOUN
fcis-25709	153	13	function	function	NOUN
fcis-25709	153	14	wcel	wcel	NOUN
fcis-25709	153	15	and	and	CCONJ
fcis-25709	153	16	the	the	DET
fcis-25709	153	17	correlation	correlation	NOUN
fcis-25709	153	18	loss	loss	NOUN
fcis-25709	153	19	i	i	PRON
fcis-25709	153	20	wcel	wcel	VERB
fcis-25709	153	21	.	.	PUNCT
fcis-25709	154	1	it	it	PRON
fcis-25709	154	2	can	can	AUX
fcis-25709	154	3	be	be	AUX
fcis-25709	154	4	expressed	express	VERB
fcis-25709	154	5	as	as	ADP
fcis-25709	154	6	:	:	PUNCT
fcis-25709	154	7	0	0	NUM
fcis-25709	154	8	1	1	NUM
fcis-25709	155	1	i	i	PRON
fcis-25709	156	1	i	i	PRON
fcis-25709	156	2	m	m	VERB
fcis-25709	156	3	wce	wce	X
fcis-25709	156	4	wce	wce	X
fcis-25709	157	1	i	i	PROPN
fcis-25709	157	2	l	l	PROPN
fcis-25709	157	3	l	l	NOUN
fcis-25709	157	4	l	l	PROPN
fcis-25709	158	1			PROPN
fcis-25709	158	2			PROPN
fcis-25709	158	3			ADJ
fcis-25709	158	4			X
fcis-25709	158	5	(	(	PUNCT
fcis-25709	158	6	16	16	NUM
fcis-25709	158	7	)	)	PUNCT
fcis-25709	158	8	fig	fig	NOUN
fcis-25709	158	9	6	6	NUM
fcis-25709	158	10	.	.	PUNCT
fcis-25709	159	1	cross	cross	ADJ
fcis-25709	159	2	-	-	ADJ
fcis-25709	159	3	layer	layer	ADJ
fcis-25709	159	4	multi	multi	ADJ
fcis-25709	159	5	-	-	ADJ
fcis-25709	159	6	loss	loss	ADJ
fcis-25709	159	7	monitoring	monitoring	NOUN
fcis-25709	159	8	module	module	NOUN
fcis-25709	159	9	where	where	SCONJ
fcis-25709	159	10			PROPN
fcis-25709	159	11	is	be	AUX
fcis-25709	159	12	the	the	DET
fcis-25709	159	13	scale	scale	NOUN
fcis-25709	159	14	factor	factor	NOUN
fcis-25709	159	15	controlling	control	VERB
fcis-25709	159	16	the	the	DET
fcis-25709	159	17	two	two	NUM
fcis-25709	159	18	loss	loss	NOUN
fcis-25709	159	19	functions	function	NOUN
fcis-25709	159	20	,	,	PUNCT
fcis-25709	159	21	i	i	PRON
fcis-25709	159	22	is	be	AUX
fcis-25709	159	23	the	the	DET
fcis-25709	159	24	number	number	NOUN
fcis-25709	159	25	of	of	ADP
fcis-25709	159	26	network	network	NOUN
fcis-25709	159	27	layers	layer	NOUN
fcis-25709	159	28	,	,	PUNCT
fcis-25709	159	29	which	which	PRON
fcis-25709	159	30	is	be	AUX
fcis-25709	159	31	set	set	VERB
fcis-25709	159	32	as	as	ADP
fcis-25709	159	33	5	5	NUM
fcis-25709	159	34	in	in	ADP
fcis-25709	159	35	this	this	DET
fcis-25709	159	36	study	study	NOUN
fcis-25709	159	37	,	,	PUNCT
fcis-25709	159	38	0	0	NUM
fcis-25709	159	39	wcel	wcel	NOUN
fcis-25709	159	40	and	and	CCONJ
fcis-25709	159	41	i	i	PRON
fcis-25709	159	42	wcel	wcel	VERB
fcis-25709	159	43	represent	represent	VERB
fcis-25709	159	44	the	the	DET
fcis-25709	159	45	output	output	NOUN
fcis-25709	159	46	loss	loss	NOUN
fcis-25709	159	47	of	of	ADP
fcis-25709	159	48	layer	layer	NOUN
fcis-25709	159	49	0	0	PUNCT
fcis-25709	160	1	and	and	CCONJ
fcis-25709	160	2	layer	layer	NOUN
fcis-25709	160	3	i	i	PRON
fcis-25709	160	4	of	of	ADP
fcis-25709	160	5	the	the	DET
fcis-25709	160	6	network	network	NOUN
fcis-25709	160	7	.	.	PUNCT
fcis-25709	161	1	3	3	X
fcis-25709	161	2	.	.	X
fcis-25709	161	3	experimental	experimental	ADJ
fcis-25709	161	4	results	result	NOUN
fcis-25709	161	5	and	and	CCONJ
fcis-25709	161	6	analysis	analysis	NOUN
fcis-25709	161	7	in	in	ADP
fcis-25709	161	8	this	this	DET
fcis-25709	161	9	paper	paper	NOUN
fcis-25709	161	10	,	,	PUNCT
fcis-25709	161	11	the	the	DET
fcis-25709	161	12	indoor	indoor	ADJ
fcis-25709	161	13	data	datum	NOUN
fcis-25709	161	14	set	set	VERB
fcis-25709	161	15	s3dis[24	s3dis[24	NOUN
fcis-25709	161	16	]	]	PUNCT
fcis-25709	161	17	is	be	AUX
fcis-25709	161	18	used	use	VERB
fcis-25709	161	19	to	to	PART
fcis-25709	161	20	verify	verify	VERB
fcis-25709	161	21	the	the	DET
fcis-25709	161	22	performance	performance	NOUN
fcis-25709	161	23	of	of	ADP
fcis-25709	161	24	mdnn	mdnn	NOUN
fcis-25709	161	25	network	network	NOUN
fcis-25709	161	26	in	in	ADP
fcis-25709	161	27	3d	3d	NUM
fcis-25709	161	28	point	point	NOUN
fcis-25709	161	29	cloud	cloud	ADJ
fcis-25709	161	30	semantic	semantic	ADJ
fcis-25709	161	31	segmentation	segmentation	NOUN
fcis-25709	161	32	task	task	NOUN
fcis-25709	161	33	.	.	PUNCT
fcis-25709	162	1	firstly	firstly	ADV
fcis-25709	162	2	,	,	PUNCT
fcis-25709	162	3	comparison	comparison	NOUN
fcis-25709	162	4	experiments	experiment	NOUN
fcis-25709	162	5	were	be	AUX
fcis-25709	162	6	conducted	conduct	VERB
fcis-25709	162	7	with	with	ADP
fcis-25709	162	8	mainstream	mainstream	NOUN
fcis-25709	162	9	networks	network	NOUN
fcis-25709	162	10	such	such	ADJ
fcis-25709	162	11	as	as	ADP
fcis-25709	162	12	pointnet[10	pointnet[10	NOUN
fcis-25709	162	13	]	]	PUNCT
fcis-25709	162	14	,	,	PUNCT
fcis-25709	162	15	randla	randla	NOUN
fcis-25709	162	16	-	-	PUNCT
fcis-25709	162	17	net[12	net[12	NOUN
fcis-25709	162	18	]	]	PUNCT
fcis-25709	162	19	and	and	CCONJ
fcis-25709	162	20	pointcnn[13	pointcnn[13	NOUN
fcis-25709	162	21	]	]	PUNCT
fcis-25709	162	22	,	,	PUNCT
fcis-25709	162	23	and	and	CCONJ
fcis-25709	162	24	then	then	ADV
fcis-25709	162	25	the	the	DET
fcis-25709	162	26	effectiveness	effectiveness	NOUN
fcis-25709	162	27	of	of	ADP
fcis-25709	162	28	each	each	DET
fcis-25709	162	29	innovation	innovation	NOUN
fcis-25709	162	30	point	point	NOUN
fcis-25709	162	31	of	of	ADP
fcis-25709	162	32	mdnn	mdnn	NOUN
fcis-25709	162	33	was	be	AUX
fcis-25709	162	34	verified	verify	VERB
fcis-25709	162	35	through	through	ADP
fcis-25709	162	36	ablation	ablation	NOUN
fcis-25709	162	37	experiments	experiment	NOUN
fcis-25709	162	38	.	.	PUNCT
fcis-25709	163	1	finally	finally	ADV
fcis-25709	163	2	,	,	PUNCT
fcis-25709	163	3	based	base	VERB
fcis-25709	163	4	on	on	ADP
fcis-25709	163	5	all	all	DET
fcis-25709	163	6	the	the	DET
fcis-25709	163	7	experimental	experimental	ADJ
fcis-25709	163	8	results	result	NOUN
fcis-25709	163	9	,	,	PUNCT
fcis-25709	163	10	the	the	DET
fcis-25709	163	11	overall	overall	ADJ
fcis-25709	163	12	performance	performance	NOUN
fcis-25709	163	13	of	of	ADP
fcis-25709	163	14	mdnn	mdnn	NOUN
fcis-25709	163	15	is	be	AUX
fcis-25709	163	16	analyzed	analyze	VERB
fcis-25709	163	17	and	and	CCONJ
fcis-25709	163	18	summarized	summarize	VERB
fcis-25709	163	19	.	.	PUNCT
fcis-25709	164	1	3.1	3.1	NUM
fcis-25709	164	2	.	.	PUNCT
fcis-25709	164	3	experimental	experimental	ADJ
fcis-25709	164	4	data	datum	NOUN
fcis-25709	164	5	set	set	VERB
fcis-25709	164	6	stanford	stanford	PROPN
fcis-25709	164	7	large	large	ADJ
fcis-25709	164	8	3d	3d	PROPN
fcis-25709	164	9	indoor	indoor	PROPN
fcis-25709	164	10	spatial	spatial	ADJ
fcis-25709	164	11	dataset	dataset	NOUN
fcis-25709	164	12	s3dis[24	s3dis[24	NOUN
fcis-25709	164	13	]	]	PUNCT
fcis-25709	164	14	is	be	AUX
fcis-25709	164	15	a	a	DET
fcis-25709	164	16	large	large	ADJ
fcis-25709	164	17	indoor	indoor	ADJ
fcis-25709	164	18	3d	3d	NOUN
fcis-25709	164	19	point	point	NOUN
fcis-25709	164	20	cloud	cloud	NOUN
fcis-25709	164	21	dataset	dataset	VERB
fcis-25709	164	22	with	with	ADP
fcis-25709	164	23	pixel	pixel	PROPN
fcis-25709	164	24	level	level	NOUN
fcis-25709	164	25	semantic	semantic	ADJ
fcis-25709	164	26	annotation	annotation	NOUN
fcis-25709	164	27	provided	provide	VERB
fcis-25709	164	28	by	by	ADP
fcis-25709	164	29	stanford	stanford	PROPN
fcis-25709	164	30	university	university	PROPN
fcis-25709	164	31	.	.	PUNCT
fcis-25709	165	1	it	it	PRON
fcis-25709	165	2	contains	contain	VERB
fcis-25709	165	3	six	six	NUM
fcis-25709	165	4	teaching	teaching	NOUN
fcis-25709	165	5	and	and	CCONJ
fcis-25709	165	6	office	office	NOUN
fcis-25709	165	7	areas	area	NOUN
fcis-25709	165	8	with	with	ADP
fcis-25709	165	9	a	a	DET
fcis-25709	165	10	total	total	NOUN
fcis-25709	165	11	of	of	ADP
fcis-25709	165	12	695,878,620	695,878,620	NUM
fcis-25709	165	13	3d	3d	NUM
fcis-25709	165	14	points	point	NOUN
fcis-25709	165	15	,	,	PUNCT
fcis-25709	165	16	with	with	ADP
fcis-25709	165	17	color	color	NOUN
fcis-25709	165	18	information	information	NOUN
fcis-25709	165	19	and	and	CCONJ
fcis-25709	165	20	semantic	semantic	ADJ
fcis-25709	165	21	labels	label	NOUN
fcis-25709	165	22	.	.	PUNCT
fcis-25709	166	1	the	the	DET
fcis-25709	166	2	data	data	NOUN
fcis-25709	166	3	is	be	AUX
fcis-25709	166	4	semantically	semantically	ADV
fcis-25709	166	5	divided	divide	VERB
fcis-25709	166	6	into	into	ADP
fcis-25709	166	7	272	272	NUM
fcis-25709	166	8	rooms	room	NOUN
fcis-25709	166	9	,	,	PUNCT
fcis-25709	166	10	annotated	annotate	VERB
fcis-25709	166	11	with	with	ADP
fcis-25709	166	12	12	12	NUM
fcis-25709	166	13	semantic	semantic	ADJ
fcis-25709	166	14	elements	element	NOUN
fcis-25709	166	15	and	and	CCONJ
fcis-25709	166	16	an	an	DET
fcis-25709	166	17	additional	additional	ADJ
fcis-25709	166	18	clutter	clutter	NOUN
fcis-25709	166	19	label	label	NOUN
fcis-25709	166	20	,	,	PUNCT
fcis-25709	166	21	and	and	CCONJ
fcis-25709	166	22	the	the	DET
fcis-25709	166	23	characteristics	characteristic	NOUN
fcis-25709	166	24	of	of	ADP
fcis-25709	166	25	the	the	DET
fcis-25709	166	26	points	point	NOUN
fcis-25709	166	27	consist	consist	VERB
fcis-25709	166	28	of	of	ADP
fcis-25709	166	29	9	9	NUM
fcis-25709	166	30	dimensions	dimension	NOUN
fcis-25709	166	31	in	in	ADP
fcis-25709	166	32	total	total	NOUN
fcis-25709	166	33	,	,	PUNCT
fcis-25709	166	34	including	include	VERB
fcis-25709	166	35	3d	3d	PROPN
fcis-25709	166	36	coordinates	coordinate	NOUN
fcis-25709	166	37	,	,	PUNCT
fcis-25709	166	38	rgb	rgb	PROPN
fcis-25709	166	39	features	feature	NOUN
fcis-25709	166	40	,	,	PUNCT
fcis-25709	166	41	and	and	CCONJ
fcis-25709	166	42	normalized	normalize	VERB
fcis-25709	166	43	positions	position	NOUN
fcis-25709	166	44	.	.	PUNCT
fcis-25709	167	1	it	it	PRON
fcis-25709	167	2	is	be	AUX
fcis-25709	167	3	commonly	commonly	ADV
fcis-25709	167	4	used	use	VERB
fcis-25709	167	5	for	for	ADP
fcis-25709	167	6	indoor	indoor	ADJ
fcis-25709	167	7	semantic	semantic	ADJ
fcis-25709	167	8	segmentation[25	segmentation[25	NOUN
fcis-25709	167	9	]	]	X
fcis-25709	167	10	.	.	PUNCT
fcis-25709	168	1	select	select	ADJ
fcis-25709	168	2	area	area	NOUN
fcis-25709	168	3	5	5	NUM
fcis-25709	168	4	as	as	SCONJ
fcis-25709	168	5	the	the	DET
fcis-25709	168	6	test	test	NOUN
fcis-25709	168	7	set	set	VERB
fcis-25709	168	8	and	and	CCONJ
fcis-25709	168	9	the	the	DET
fcis-25709	168	10	rest	rest	NOUN
fcis-25709	168	11	as	as	ADP
fcis-25709	168	12	the	the	DET
fcis-25709	168	13	training	training	NOUN
fcis-25709	168	14	set	set	NOUN
fcis-25709	168	15	.	.	PUNCT
fcis-25709	169	1	the	the	DET
fcis-25709	169	2	data	datum	NOUN
fcis-25709	169	3	in	in	ADP
fcis-25709	169	4	region	region	NOUN
fcis-25709	169	5	5	5	NUM
fcis-25709	169	6	and	and	CCONJ
fcis-25709	169	7	other	other	ADJ
fcis-25709	169	8	regions	region	NOUN
fcis-25709	169	9	are	be	AUX
fcis-25709	169	10	not	not	PART
fcis-25709	169	11	in	in	ADP
fcis-25709	169	12	the	the	DET
fcis-25709	169	13	same	same	ADJ
fcis-25709	169	14	building	building	NOUN
fcis-25709	169	15	,	,	PUNCT
fcis-25709	169	16	and	and	CCONJ
fcis-25709	169	17	there	there	PRON
fcis-25709	169	18	are	be	VERB
fcis-25709	169	19	certain	certain	ADJ
fcis-25709	169	20	differences	difference	NOUN
fcis-25709	169	21	in	in	ADP
fcis-25709	169	22	the	the	DET
fcis-25709	169	23	objects	object	NOUN
fcis-25709	169	24	in	in	ADP
fcis-25709	169	25	the	the	DET
fcis-25709	169	26	scene	scene	NOUN
fcis-25709	169	27	.	.	PUNCT
fcis-25709	170	1	this	this	DET
fcis-25709	170	2	division	division	NOUN
fcis-25709	170	3	can	can	AUX
fcis-25709	170	4	more	more	ADV
fcis-25709	170	5	accurately	accurately	ADV
fcis-25709	170	6	test	test	VERB
fcis-25709	170	7	the	the	DET
fcis-25709	170	8	accuracy	accuracy	NOUN
fcis-25709	170	9	of	of	ADP
fcis-25709	170	10	mdnn	mdnn	NOUN
fcis-25709	170	11	semantic	semantic	ADJ
fcis-25709	170	12	segmentation	segmentation	NOUN
fcis-25709	170	13	and	and	CCONJ
fcis-25709	170	14	the	the	DET
fcis-25709	170	15	generalization	generalization	NOUN
fcis-25709	170	16	ability	ability	NOUN
fcis-25709	170	17	of	of	ADP
fcis-25709	170	18	point	point	NOUN
fcis-25709	170	19	cloud	cloud	NOUN
fcis-25709	170	20	data	datum	NOUN
fcis-25709	170	21	recognition	recognition	NOUN
fcis-25709	170	22	.	.	PUNCT
fcis-25709	171	1	3.2	3.2	NUM
fcis-25709	171	2	.	.	PUNCT
fcis-25709	171	3	environment	environment	NOUN
fcis-25709	171	4	configuration	configuration	NOUN
fcis-25709	171	5	and	and	CCONJ
fcis-25709	171	6	evaluation	evaluation	NOUN
fcis-25709	171	7	indicators	indicator	NOUN
fcis-25709	171	8	the	the	DET
fcis-25709	171	9	network	network	NOUN
fcis-25709	171	10	proposed	propose	VERB
fcis-25709	171	11	in	in	ADP
fcis-25709	171	12	this	this	DET
fcis-25709	171	13	study	study	NOUN
fcis-25709	171	14	trained	train	VERB
fcis-25709	171	15	200	200	NUM
fcis-25709	171	16	rounds	round	NOUN
fcis-25709	171	17	on	on	ADP
fcis-25709	171	18	two	two	NUM
fcis-25709	171	19	geforce	geforce	NOUN
fcis-25709	171	20	rtx	rtx	PROPN
fcis-25709	171	21	3090	3090	NUM
fcis-25709	171	22	gpus	gpu	NOUN
fcis-25709	171	23	(	(	PUNCT
fcis-25709	171	24	24	24	NUM
fcis-25709	171	25	gb	gb	PROPN
fcis-25709	171	26	video	video	NOUN
fcis-25709	171	27	memory	memory	NOUN
fcis-25709	171	28	)	)	PUNCT
fcis-25709	171	29	.	.	PUNCT
fcis-25709	172	1	the	the	DET
fcis-25709	172	2	16	16	NUM
fcis-25709	172	3	cuda10.6	cuda10.6	NOUN
fcis-25709	172	4	gpu	gpu	X
fcis-25709	172	5	running	running	NOUN
fcis-25709	172	6	environment	environment	NOUN
fcis-25709	172	7	was	be	AUX
fcis-25709	172	8	built	build	VERB
fcis-25709	172	9	on	on	ADP
fcis-25709	172	10	ubuntu20.04	ubuntu20.04	PROPN
fcis-25709	172	11	system	system	NOUN
fcis-25709	172	12	,	,	PUNCT
fcis-25709	172	13	and	and	CCONJ
fcis-25709	172	14	the	the	DET
fcis-25709	172	15	deep	deep	ADJ
fcis-25709	172	16	learning	learning	NOUN
fcis-25709	172	17	framework	framework	NOUN
fcis-25709	172	18	was	be	AUX
fcis-25709	172	19	based	base	VERB
fcis-25709	172	20	on	on	ADP
fcis-25709	172	21	python	python	NOUN
fcis-25709	172	22	and	and	CCONJ
fcis-25709	172	23	pytorch	pytorch	NOUN
fcis-25709	172	24	platform	platform	NOUN
fcis-25709	172	25	.	.	PUNCT
fcis-25709	173	1	in	in	ADP
fcis-25709	173	2	this	this	DET
fcis-25709	173	3	paper	paper	NOUN
fcis-25709	173	4	,	,	PUNCT
fcis-25709	173	5	the	the	DET
fcis-25709	173	6	nearest	near	ADJ
fcis-25709	173	7	neighbor	neighbor	NOUN
fcis-25709	173	8	point	point	NOUN
fcis-25709	173	9	k	k	PROPN
fcis-25709	173	10	value	value	NOUN
fcis-25709	173	11	used	use	VERB
fcis-25709	173	12	in	in	ADP
fcis-25709	173	13	the	the	DET
fcis-25709	173	14	training	training	NOUN
fcis-25709	173	15	and	and	CCONJ
fcis-25709	173	16	testing	testing	NOUN
fcis-25709	173	17	model	model	NOUN
fcis-25709	173	18	is	be	AUX
fcis-25709	173	19	16	16	NUM
fcis-25709	173	20	,	,	PUNCT
fcis-25709	173	21	the	the	DET
fcis-25709	173	22	learning	learn	VERB
fcis-25709	173	23	rate	rate	NOUN
fcis-25709	173	24	starts	start	VERB
fcis-25709	173	25	from	from	ADP
fcis-25709	173	26	0.01	0.01	NUM
fcis-25709	173	27	,	,	PUNCT
fcis-25709	173	28	decutes	decute	VERB
fcis-25709	173	29	at	at	ADP
fcis-25709	173	30	a	a	DET
fcis-25709	173	31	rate	rate	NOUN
fcis-25709	173	32	of	of	ADP
fcis-25709	173	33	0.3	0.3	NUM
fcis-25709	173	34	after	after	ADP
fcis-25709	173	35	every	every	DET
fcis-25709	173	36	10	10	NUM
fcis-25709	173	37	rounds	round	NOUN
fcis-25709	173	38	,	,	PUNCT
fcis-25709	173	39	and	and	CCONJ
fcis-25709	173	40	the	the	DET
fcis-25709	173	41	momentum	momentum	NOUN
fcis-25709	173	42	is	be	AUX
fcis-25709	173	43	0.95	0.95	NUM
fcis-25709	173	44	.	.	PUNCT
fcis-25709	174	1	adam	adam	PROPN
fcis-25709	174	2	optimization	optimization	NOUN
fcis-25709	174	3	algorithm	algorithm	NOUN
fcis-25709	174	4	is	be	AUX
fcis-25709	174	5	used	use	VERB
fcis-25709	174	6	to	to	PART
fcis-25709	174	7	minimize	minimize	VERB
fcis-25709	174	8	the	the	DET
fcis-25709	174	9	loss	loss	NOUN
fcis-25709	174	10	function	function	NOUN
fcis-25709	174	11	.	.	PUNCT
fcis-25709	175	1	this	this	DET
fcis-25709	175	2	paper	paper	NOUN
fcis-25709	175	3	follows	follow	VERB
fcis-25709	175	4	the	the	DET
fcis-25709	175	5	standard	standard	ADJ
fcis-25709	175	6	practice	practice	NOUN
fcis-25709	175	7	of	of	ADP
fcis-25709	175	8	isprs[26	isprs[26	NOUN
fcis-25709	175	9	]	]	X
fcis-25709	175	10	(	(	PUNCT
fcis-25709	175	11	international	international	ADJ
fcis-25709	175	12	society	society	NOUN
fcis-25709	175	13	for	for	ADP
fcis-25709	175	14	photogrammetry	photogrammetry	NOUN
fcis-25709	175	15	and	and	CCONJ
fcis-25709	175	16	remote	remote	ADJ
fcis-25709	175	17	sensing	sensing	NOUN
fcis-25709	175	18	)	)	PUNCT
fcis-25709	175	19	competition	competition	NOUN
fcis-25709	175	20	,	,	PUNCT
fcis-25709	175	21	using	use	VERB
fcis-25709	175	22	mean	mean	NOUN
fcis-25709	175	23	crossover	crossover	NOUN
fcis-25709	175	24	ratio	ratio	NOUN
fcis-25709	175	25	(	(	PUNCT
fcis-25709	175	26	miou	miou	NOUN
fcis-25709	175	27	)	)	PUNCT
fcis-25709	175	28	,	,	PUNCT
fcis-25709	175	29	class	class	NOUN
fcis-25709	175	30	mean	mean	NOUN
fcis-25709	175	31	accuracy	accuracy	NOUN
fcis-25709	175	32	(	(	PUNCT
fcis-25709	175	33	macc	macc	PROPN
fcis-25709	175	34	)	)	PUNCT
fcis-25709	175	35	and	and	CCONJ
fcis-25709	175	36	overall	overall	ADJ
fcis-25709	175	37	accuracy	accuracy	NOUN
fcis-25709	175	38	(	(	PUNCT
fcis-25709	175	39	oa	oa	INTJ
fcis-25709	175	40	)	)	PUNCT
fcis-25709	175	41	as	as	ADP
fcis-25709	175	42	evaluation	evaluation	NOUN
fcis-25709	175	43	indicators	indicator	NOUN
fcis-25709	175	44	.	.	PUNCT
fcis-25709	176	1	miou	miou	NOUN
fcis-25709	176	2	represents	represent	VERB
fcis-25709	176	3	the	the	DET
fcis-25709	176	4	intersection	intersection	NOUN
fcis-25709	176	5	/	/	SYM
fcis-25709	176	6	union	union	NOUN
fcis-25709	176	7	of	of	ADP
fcis-25709	176	8	true	true	ADJ
fcis-25709	176	9	values	value	NOUN
fcis-25709	176	10	and	and	CCONJ
fcis-25709	176	11	predicted	predict	VERB
fcis-25709	176	12	values	value	NOUN
fcis-25709	176	13	,	,	PUNCT
fcis-25709	176	14	and	and	CCONJ
fcis-25709	176	15	is	be	AUX
fcis-25709	176	16	used	use	VERB
fcis-25709	176	17	to	to	PART
fcis-25709	176	18	evaluate	evaluate	VERB
fcis-25709	176	19	the	the	DET
fcis-25709	176	20	accuracy	accuracy	NOUN
fcis-25709	176	21	of	of	ADP
fcis-25709	176	22	all	all	DET
fcis-25709	176	23	object	object	NOUN
fcis-25709	176	24	class	class	NOUN
fcis-25709	176	25	segmentation	segmentation	NOUN
fcis-25709	176	26	;	;	PUNCT
fcis-25709	176	27	macc	macc	PROPN
fcis-25709	176	28	represents	represent	VERB
fcis-25709	176	29	the	the	DET
fcis-25709	176	30	average	average	ADJ
fcis-25709	176	31	recognition	recognition	NOUN
fcis-25709	176	32	accuracy	accuracy	NOUN
fcis-25709	176	33	of	of	ADP
fcis-25709	176	34	the	the	DET
fcis-25709	176	35	model	model	NOUN
fcis-25709	176	36	for	for	ADP
fcis-25709	176	37	each	each	DET
fcis-25709	176	38	category	category	NOUN
fcis-25709	176	39	,	,	PUNCT
fcis-25709	176	40	and	and	CCONJ
fcis-25709	176	41	is	be	AUX
fcis-25709	176	42	used	use	VERB
fcis-25709	176	43	to	to	PART
fcis-25709	176	44	measure	measure	VERB
fcis-25709	176	45	whether	whether	SCONJ
fcis-25709	176	46	the	the	DET
fcis-25709	176	47	recognition	recognition	NOUN
fcis-25709	176	48	ability	ability	NOUN
fcis-25709	176	49	of	of	ADP
fcis-25709	176	50	the	the	DET
fcis-25709	176	51	model	model	NOUN
fcis-25709	176	52	for	for	ADP
fcis-25709	176	53	all	all	DET
fcis-25709	176	54	categories	category	NOUN
fcis-25709	176	55	is	be	AUX
fcis-25709	176	56	balanced	balanced	ADJ
fcis-25709	176	57	.	.	PUNCT
fcis-25709	177	1	oa	oa	PROPN
fcis-25709	177	2	represents	represent	VERB
fcis-25709	177	3	the	the	DET
fcis-25709	177	4	percentage	percentage	NOUN
fcis-25709	177	5	of	of	ADP
fcis-25709	177	6	the	the	DET
fcis-25709	177	7	total	total	ADJ
fcis-25709	177	8	input	input	NOUN
fcis-25709	177	9	category	category	NOUN
fcis-25709	177	10	that	that	PRON
fcis-25709	177	11	predicts	predict	VERB
fcis-25709	177	12	the	the	DET
fcis-25709	177	13	correct	correct	ADJ
fcis-25709	177	14	category	category	NOUN
fcis-25709	177	15	and	and	CCONJ
fcis-25709	177	16	is	be	AUX
fcis-25709	177	17	used	use	VERB
fcis-25709	177	18	to	to	PART
fcis-25709	177	19	assess	assess	VERB
fcis-25709	177	20	the	the	DET
fcis-25709	177	21	accuracy	accuracy	NOUN
fcis-25709	177	22	of	of	ADP
fcis-25709	177	23	the	the	DET
fcis-25709	177	24	overall	overall	ADJ
fcis-25709	177	25	segmentation	segmentation	NOUN
fcis-25709	177	26	.	.	PUNCT
fcis-25709	178	1	assume	assume	VERB
fcis-25709	178	2	that	that	SCONJ
fcis-25709	178	3	tp	tp	NOUN
fcis-25709	178	4	,	,	PUNCT
fcis-25709	178	5	fp	fp	PROPN
fcis-25709	178	6	,	,	PUNCT
fcis-25709	178	7	tn	tn	PROPN
fcis-25709	178	8	,	,	PUNCT
fcis-25709	178	9	and	and	CCONJ
fcis-25709	178	10	fn	fn	AUX
fcis-25709	178	11	represent	represent	VERB
fcis-25709	178	12	true	true	ADJ
fcis-25709	178	13	,	,	PUNCT
fcis-25709	178	14	false	false	ADJ
fcis-25709	178	15	positive	positive	ADJ
fcis-25709	178	16	,	,	PUNCT
fcis-25709	178	17	true	true	ADJ
fcis-25709	178	18	negative	negative	ADJ
fcis-25709	178	19	,	,	PUNCT
fcis-25709	178	20	and	and	CCONJ
fcis-25709	178	21	false	false	ADJ
fcis-25709	178	22	negative	negative	ADJ
fcis-25709	178	23	respectively	respectively	ADV
fcis-25709	178	24	,	,	PUNCT
fcis-25709	178	25	and	and	CCONJ
fcis-25709	178	26	k	k	PROPN
fcis-25709	178	27	represents	represent	VERB
fcis-25709	178	28	the	the	DET
fcis-25709	178	29	number	number	NOUN
fcis-25709	178	30	of	of	ADP
fcis-25709	178	31	semantic	semantic	ADJ
fcis-25709	178	32	categories	category	NOUN
fcis-25709	178	33	in	in	ADP
fcis-25709	178	34	the	the	DET
fcis-25709	178	35	dataset	dataset	NOUN
fcis-25709	178	36	.	.	PUNCT
fcis-25709	179	1	its	its	PRON
fcis-25709	179	2	calculation	calculation	NOUN
fcis-25709	179	3	formula	formula	NOUN
fcis-25709	179	4	is	be	AUX
fcis-25709	179	5	as	as	SCONJ
fcis-25709	179	6	follows	follow	VERB
fcis-25709	179	7	:	:	PUNCT
fcis-25709	180	1	0	0	NUM
fcis-25709	180	2	1	1	NUM
fcis-25709	180	3	1	1	NUM
fcis-25709	180	4	k	k	NOUN
fcis-25709	181	1	i	i	PRON
fcis-25709	181	2	tp	tp	VERB
fcis-25709	181	3	miou	miou	PROPN
fcis-25709	182	1	k	k	PROPN
fcis-25709	182	2	tp	tp	PROPN
fcis-25709	182	3	fp	fp	PROPN
fcis-25709	182	4	fn	fn	PROPN
fcis-25709	182	5			PROPN
fcis-25709	182	6			ADV
fcis-25709	182	7			PUNCT
fcis-25709	182	8			NOUN
fcis-25709	182	9	(	(	PUNCT
fcis-25709	182	10	17	17	NUM
fcis-25709	182	11	)	)	PUNCT
fcis-25709	182	12	0	0	NUM
fcis-25709	182	13	1	1	NUM
fcis-25709	182	14	1	1	NUM
fcis-25709	182	15	k	k	NOUN
fcis-25709	183	1	i	i	PRON
fcis-25709	183	2	i	i	PRON
fcis-25709	184	1	i	i	PRON
fcis-25709	184	2	i	i	PRON
fcis-25709	185	1	tp	tp	VERB
fcis-25709	185	2	macc	macc	PROPN
fcis-25709	185	3	k	k	PROPN
fcis-25709	185	4	tp	tp	PROPN
fcis-25709	185	5	fn	fn	PROPN
fcis-25709	185	6			PROPN
fcis-25709	185	7			ADJ
fcis-25709	185	8			NOUN
fcis-25709	185	9	(	(	PUNCT
fcis-25709	185	10	18	18	NUM
fcis-25709	185	11	)	)	PUNCT
fcis-25709	185	12	tp	tp	ADP
fcis-25709	185	13	tn	tn	NOUN
fcis-25709	185	14	oa	oa	INTJ
fcis-25709	185	15	tp	tp	ADP
fcis-25709	185	16	fp	fp	PROPN
fcis-25709	185	17	fn	fn	PROPN
fcis-25709	185	18	tn	tn	PROPN
fcis-25709	185	19			PROPN
fcis-25709	185	20			PROPN
fcis-25709	185	21			PROPN
fcis-25709	185	22			PUNCT
fcis-25709	185	23			X
fcis-25709	185	24	(	(	PUNCT
fcis-25709	185	25	19	19	NUM
fcis-25709	185	26	)	)	PUNCT
fcis-25709	185	27	3.3	3.3	NUM
fcis-25709	185	28	.	.	PUNCT
fcis-25709	186	1	analysis	analysis	NOUN
fcis-25709	186	2	of	of	ADP
fcis-25709	186	3	experimental	experimental	ADJ
fcis-25709	186	4	results	result	NOUN
fcis-25709	186	5	in	in	ADP
fcis-25709	186	6	this	this	DET
fcis-25709	186	7	paper	paper	NOUN
fcis-25709	186	8	,	,	PUNCT
fcis-25709	186	9	the	the	DET
fcis-25709	186	10	performance	performance	NOUN
fcis-25709	186	11	of	of	ADP
fcis-25709	186	12	mdnn	mdnn	NOUN
fcis-25709	186	13	on	on	ADP
fcis-25709	186	14	large	large	ADJ
fcis-25709	186	15	-	-	PUNCT
fcis-25709	186	16	scale	scale	NOUN
fcis-25709	186	17	scene	scene	NOUN
fcis-25709	186	18	semantic	semantic	ADJ
fcis-25709	186	19	segmentation	segmentation	NOUN
fcis-25709	186	20	task	task	NOUN
fcis-25709	186	21	was	be	AUX
fcis-25709	186	22	tested	test	VERB
fcis-25709	186	23	on	on	ADP
fcis-25709	186	24	s3dis	s3dis	PROPN
fcis-25709	186	25	point	point	NOUN
fcis-25709	186	26	cloud	cloud	NOUN
fcis-25709	186	27	dataset	dataset	NOUN
fcis-25709	186	28	.	.	PUNCT
fcis-25709	187	1	table	table	NOUN
fcis-25709	187	2	1	1	NUM
fcis-25709	187	3	shows	show	VERB
fcis-25709	187	4	the	the	DET
fcis-25709	187	5	comparison	comparison	NOUN
fcis-25709	187	6	of	of	ADP
fcis-25709	187	7	evaluation	evaluation	NOUN
fcis-25709	187	8	indexes	index	NOUN
fcis-25709	187	9	of	of	ADP
fcis-25709	187	10	semantic	semantic	ADJ
fcis-25709	187	11	segmentation	segmentation	NOUN
fcis-25709	187	12	between	between	ADP
fcis-25709	187	13	the	the	DET
fcis-25709	187	14	network	network	NOUN
fcis-25709	187	15	in	in	ADP
fcis-25709	187	16	this	this	DET
fcis-25709	187	17	paper	paper	NOUN
fcis-25709	187	18	and	and	CCONJ
fcis-25709	187	19	nine	nine	NUM
fcis-25709	187	20	advanced	advanced	ADJ
fcis-25709	187	21	networks	network	NOUN
fcis-25709	187	22	.	.	PUNCT
fcis-25709	188	1	table	table	NOUN
fcis-25709	188	2	1	1	NUM
fcis-25709	188	3	.	.	PUNCT
fcis-25709	189	1	quantitative	quantitative	ADJ
fcis-25709	189	2	experimental	experimental	ADJ
fcis-25709	189	3	results	result	NOUN
fcis-25709	189	4	of	of	ADP
fcis-25709	189	5	different	different	ADJ
fcis-25709	189	6	networks	network	NOUN
fcis-25709	189	7	on	on	ADP
fcis-25709	189	8	the	the	DET
fcis-25709	189	9	s3dis	s3dis	PROPN
fcis-25709	189	10	dataset	dataset	NOUN
fcis-25709	189	11	(	(	PUNCT
fcis-25709	189	12	6	6	NUM
fcis-25709	189	13	-	-	ADJ
fcis-25709	189	14	fold	fold	ADJ
fcis-25709	189	15	cross	cross	ADJ
fcis-25709	189	16	-	-	ADJ
fcis-25709	189	17	validation	validation	ADJ
fcis-25709	189	18	)	)	PUNCT
fcis-25709	189	19	network	network	NOUN
fcis-25709	189	20	miou(%	miou(%	PROPN
fcis-25709	189	21	)	)	PUNCT
fcis-25709	189	22	macc	macc	NOUN
fcis-25709	189	23	(	(	PUNCT
fcis-25709	189	24	%	%	INTJ
fcis-25709	189	25	)	)	PUNCT
fcis-25709	190	1	oa	oa	PROPN
fcis-25709	190	2	(	(	PUNCT
fcis-25709	190	3	%	%	INTJ
fcis-25709	190	4	)	)	PUNCT
fcis-25709	190	5	pointnet[10	pointnet[10	NOUN
fcis-25709	190	6	]	]	PUNCT
fcis-25709	191	1	47.6	47.6	NUM
fcis-25709	191	2	66.2	66.2	NUM
fcis-25709	191	3	78.6	78.6	NUM
fcis-25709	191	4	pointnet++[11	pointnet++[11	PROPN
fcis-25709	191	5	]	]	X
fcis-25709	191	6	54.5	54.5	NUM
fcis-25709	191	7	67.1	67.1	NUM
fcis-25709	191	8	81.0	81.0	NUM
fcis-25709	191	9	dgcnn[27	dgcnn[27	NOUN
fcis-25709	191	10	]	]	PUNCT
fcis-25709	192	1	56.1	56.1	NUM
fcis-25709	192	2	84.1	84.1	NUM
fcis-25709	192	3	pointcnn[13	pointcnn[13	NOUN
fcis-25709	192	4	]	]	PUNCT
fcis-25709	192	5	65.4	65.4	NUM
fcis-25709	192	6	75.6	75.6	NUM
fcis-25709	192	7	88.1	88.1	NUM
fcis-25709	192	8	ga	ga	NOUN
fcis-25709	192	9	-	-	PUNCT
fcis-25709	192	10	net[28	net[28	X
fcis-25709	192	11	]	]	PUNCT
fcis-25709	192	12	63.7	63.7	NUM
fcis-25709	192	13	87.6	87.6	NUM
fcis-25709	192	14	pointweb[29	pointweb[29	NOUN
fcis-25709	192	15	]	]	X
fcis-25709	192	16	66.7	66.7	NUM
fcis-25709	192	17	76.2	76.2	NUM
fcis-25709	192	18	87.3	87.3	NUM
fcis-25709	192	19	randla	randla	NOUN
fcis-25709	192	20	-	-	PUNCT
fcis-25709	192	21	net[12	net[12	NOUN
fcis-25709	192	22	]	]	PUNCT
fcis-25709	192	23	70.0	70.0	NUM
fcis-25709	192	24	82.0	82.0	NUM
fcis-25709	192	25	88.0	88.0	NUM
fcis-25709	192	26	baf	baf	PROPN
fcis-25709	192	27	-	-	PUNCT
fcis-25709	192	28	lac[30	lac[30	PROPN
fcis-25709	192	29	]	]	X
fcis-25709	192	30	71.7	71.7	NUM
fcis-25709	192	31	82.5	82.5	NUM
fcis-25709	192	32	88.2	88.2	NUM
fcis-25709	192	33	scf	scf	PROPN
fcis-25709	192	34	-	-	PUNCT
fcis-25709	192	35	net[31	net[31	X
fcis-25709	192	36	]	]	X
fcis-25709	192	37	71.6	71.6	NUM
fcis-25709	192	38	82.7	82.7	NUM
fcis-25709	192	39	88.4	88.4	NUM
fcis-25709	192	40	mdnn	mdnn	NOUN
fcis-25709	192	41	71.2	71.2	NUM
fcis-25709	192	42	83.9	83.9	NUM
fcis-25709	192	43	88.7	88.7	NUM
fcis-25709	192	44	table	table	NOUN
fcis-25709	192	45	2	2	NUM
fcis-25709	192	46	.	.	PUNCT
fcis-25709	192	47	quantitative	quantitative	ADJ
fcis-25709	192	48	evaluation	evaluation	NOUN
fcis-25709	192	49	results	result	NOUN
fcis-25709	192	50	of	of	ADP
fcis-25709	192	51	s3dis	s3di	NOUN
fcis-25709	192	52	dataset	dataset	VERB
fcis-25709	192	53	area5	area5	PROPN
fcis-25709	192	54	network	network	NOUN
fcis-25709	192	55	ceiling	ceiling	PROPN
fcis-25709	192	56	floor	floor	PROPN
fcis-25709	192	57	wall	wall	PROPN
fcis-25709	192	58	beam	beam	PROPN
fcis-25709	192	59	col	col	PROPN
fcis-25709	192	60	wind	wind	PROPN
fcis-25709	192	61	door	door	NOUN
fcis-25709	192	62	table	table	NOUN
fcis-25709	192	63	chair	chair	NOUN
fcis-25709	192	64	sofa	sofa	NOUN
fcis-25709	192	65	book	book	NOUN
fcis-25709	192	66	board	board	NOUN
fcis-25709	192	67	clutter	clutter	NOUN
fcis-25709	192	68	pointnet	pointnet	NOUN
fcis-25709	192	69	[	[	X
fcis-25709	192	70	10	10	NUM
fcis-25709	192	71	]	]	SYM
fcis-25709	192	72	88.8	88.8	NUM
fcis-25709	192	73	97.3	97.3	NUM
fcis-25709	192	74	69.8	69.8	NUM
fcis-25709	192	75	0.1	0.1	NUM
fcis-25709	192	76	3.9	3.9	NUM
fcis-25709	192	77	46.3	46.3	NUM
fcis-25709	192	78	10.8	10.8	NUM
fcis-25709	192	79	59.0	59.0	NUM
fcis-25709	192	80	52.6	52.6	NUM
fcis-25709	192	81	5.9	5.9	NUM
fcis-25709	192	82	40.3	40.3	NUM
fcis-25709	192	83	26.4	26.4	NUM
fcis-25709	192	84	33.2	33.2	NUM
fcis-25709	192	85	pointnet+	pointnet+	NOUN
fcis-25709	193	1	+	+	CCONJ
fcis-25709	193	2	[	[	X
fcis-25709	193	3	11	11	NUM
fcis-25709	193	4	]	]	SYM
fcis-25709	193	5	90.7	90.7	NUM
fcis-25709	193	6	96.3	96.3	NUM
fcis-25709	193	7	74.2	74.2	NUM
fcis-25709	193	8	0.0	0.0	NUM
fcis-25709	193	9	7.8	7.8	NUM
fcis-25709	193	10	57.5	57.5	NUM
fcis-25709	193	11	23.4	23.4	NUM
fcis-25709	193	12	66.6	66.6	NUM
fcis-25709	193	13	70.4	70.4	NUM
fcis-25709	193	14	42.0	42.0	NUM
fcis-25709	193	15	61.0	61.0	NUM
fcis-25709	193	16	53.3	53.3	NUM
fcis-25709	193	17	41.2	41.2	NUM
fcis-25709	193	18	dgcnn	dgcnn	NOUN
fcis-25709	193	19	[	[	X
fcis-25709	193	20	27	27	NUM
fcis-25709	193	21	]	]	SYM
fcis-25709	193	22	93.0	93.0	NUM
fcis-25709	193	23	97.4	97.4	NUM
fcis-25709	193	24	77.7	77.7	NUM
fcis-25709	193	25	0.0	0.0	NUM
fcis-25709	193	26	12.0	12.0	NUM
fcis-25709	193	27	47.8	47.8	NUM
fcis-25709	193	28	39.8	39.8	NUM
fcis-25709	193	29	67.4	67.4	NUM
fcis-25709	193	30	72.4	72.4	NUM
fcis-25709	193	31	23.2	23.2	NUM
fcis-25709	193	32	52.3	52.3	NUM
fcis-25709	193	33	39.8	39.8	NUM
fcis-25709	193	34	46.6	46.6	NUM
fcis-25709	193	35	pointcnn	pointcnn	NOUN
fcis-25709	193	36	[	[	X
fcis-25709	193	37	13	13	NUM
fcis-25709	193	38	]	]	SYM
fcis-25709	193	39	92.3	92.3	NUM
fcis-25709	193	40	98.2	98.2	NUM
fcis-25709	193	41	79.4	79.4	NUM
fcis-25709	193	42	0.0	0.0	NUM
fcis-25709	193	43	17.6	17.6	NUM
fcis-25709	193	44	22.8	22.8	NUM
fcis-25709	193	45	62.1	62.1	NUM
fcis-25709	193	46	74.4	74.4	NUM
fcis-25709	193	47	80.6	80.6	NUM
fcis-25709	193	48	31.7	31.7	NUM
fcis-25709	193	49	66.7	66.7	NUM
fcis-25709	193	50	62.1	62.1	NUM
fcis-25709	193	51	56.7	56.7	NUM
fcis-25709	193	52	ga	ga	NOUN
fcis-25709	193	53	-	-	NOUN
fcis-25709	193	54	net	net	NOUN
fcis-25709	193	55	[	[	X
fcis-25709	193	56	28	28	NUM
fcis-25709	193	57	]	]	SYM
fcis-25709	194	1	92.9	92.9	NUM
fcis-25709	194	2	97.8	97.8	NUM
fcis-25709	194	3	81.3	81.3	NUM
fcis-25709	194	4	0.0	0.0	NUM
fcis-25709	194	5	27.8	27.8	NUM
fcis-25709	194	6	60.3	60.3	NUM
fcis-25709	194	7	41.7	41.7	NUM
fcis-25709	194	8	78.3	78.3	NUM
fcis-25709	194	9	86.7	86.7	NUM
fcis-25709	194	10	71.4	71.4	NUM
fcis-25709	194	11	69.9	69.9	NUM
fcis-25709	194	12	65.8	65.8	NUM
fcis-25709	194	13	53.9	53.9	NUM
fcis-25709	194	14	pointweb	pointweb	NOUN
fcis-25709	195	1	[	[	X
fcis-25709	195	2	29	29	NUM
fcis-25709	195	3	]	]	PUNCT
fcis-25709	195	4	92.0	92.0	NUM
fcis-25709	195	5	98.5	98.5	NUM
fcis-25709	195	6	79.4	79.4	NUM
fcis-25709	195	7	0.0	0.0	NUM
fcis-25709	195	8	21.1	21.1	NUM
fcis-25709	195	9	59.7	59.7	NUM
fcis-25709	195	10	34.8	34.8	NUM
fcis-25709	195	11	76.3	76.3	NUM
fcis-25709	195	12	88.3	88.3	NUM
fcis-25709	195	13	46.9	46.9	NUM
fcis-25709	195	14	69.3	69.3	NUM
fcis-25709	195	15	64.9	64.9	NUM
fcis-25709	195	16	52.5	52.5	NUM
fcis-25709	195	17	randlanet	randlanet	NOUN
fcis-25709	195	18	[	[	X
fcis-25709	195	19	12	12	NUM
fcis-25709	195	20	]	]	SYM
fcis-25709	195	21	91.1	91.1	NUM
fcis-25709	195	22	95.6	95.6	NUM
fcis-25709	195	23	80.2	80.2	NUM
fcis-25709	195	24	0.0	0.0	NUM
fcis-25709	195	25	24.7	24.7	NUM
fcis-25709	195	26	62.3	62.3	NUM
fcis-25709	195	27	47.7	47.7	NUM
fcis-25709	195	28	76.2	76.2	NUM
fcis-25709	195	29	83.7	83.7	NUM
fcis-25709	195	30	60.2	60.2	NUM
fcis-25709	195	31	71.2	71.2	NUM
fcis-25709	195	32	70.1	70.1	NUM
fcis-25709	195	33	53.9	53.9	NUM
fcis-25709	195	34	baf	baf	NOUN
fcis-25709	195	35	-	-	PUNCT
fcis-25709	195	36	lac	lac	PROPN
fcis-25709	196	1	[	[	X
fcis-25709	196	2	30	30	NUM
fcis-25709	196	3	]	]	SYM
fcis-25709	196	4	91.2	91.2	NUM
fcis-25709	196	5	87.3	87.3	NUM
fcis-25709	196	6	81.6	81.6	NUM
fcis-25709	196	7	0.0	0.0	NUM
fcis-25709	196	8	27.9	27.9	NUM
fcis-25709	196	9	59.3	59.3	NUM
fcis-25709	196	10	49.5	49.5	NUM
fcis-25709	196	11	78.0	78.0	NUM
fcis-25709	196	12	87.2	87.2	NUM
fcis-25709	196	13	63.4	63.4	NUM
fcis-25709	196	14	66.5	66.5	NUM
fcis-25709	196	15	69.6	69.6	NUM
fcis-25709	196	16	51.1	51.1	NUM
fcis-25709	196	17	scf	scf	PROPN
fcis-25709	196	18	-	-	PUNCT
fcis-25709	196	19	net	net	NOUN
fcis-25709	196	20	[	[	X
fcis-25709	196	21	31	31	NUM
fcis-25709	196	22	]	]	SYM
fcis-25709	196	23	94.3	94.3	NUM
fcis-25709	196	24	98.4	98.4	NUM
fcis-25709	196	25	84.2	84.2	NUM
fcis-25709	196	26	0.0	0.0	NUM
fcis-25709	196	27	28.3	28.3	NUM
fcis-25709	196	28	58.9	58.9	NUM
fcis-25709	196	29	73.2	73.2	NUM
fcis-25709	196	30	92.2	92.2	NUM
fcis-25709	196	31	82.9	82.9	NUM
fcis-25709	196	32	76.6	76.6	NUM
fcis-25709	196	33	82.2	82.2	NUM
fcis-25709	196	34	68.6	68.6	NUM
fcis-25709	196	35	59.9	59.9	NUM
fcis-25709	196	36	mdnn	mdnn	NOUN
fcis-25709	196	37	93.8	93.8	NUM
fcis-25709	196	38	98.6	98.6	NUM
fcis-25709	196	39	82.4	82.4	NUM
fcis-25709	196	40	0.0	0.0	NUM
fcis-25709	196	41	27.7	27.7	NUM
fcis-25709	196	42	63.1	63.1	NUM
fcis-25709	196	43	71.6	71.6	NUM
fcis-25709	196	44	89.4	89.4	NUM
fcis-25709	196	45	85.5	85.5	NUM
fcis-25709	196	46	73.8	73.8	NUM
fcis-25709	196	47	79.3	79.3	NUM
fcis-25709	196	48	70.3	70.3	NUM
fcis-25709	196	49	55.9	55.9	NUM
fcis-25709	196	50	as	as	SCONJ
fcis-25709	196	51	can	can	AUX
fcis-25709	196	52	be	be	AUX
fcis-25709	196	53	seen	see	VERB
fcis-25709	196	54	from	from	ADP
fcis-25709	196	55	table	table	NOUN
fcis-25709	196	56	1	1	NUM
fcis-25709	196	57	,	,	PUNCT
fcis-25709	196	58	in	in	ADP
fcis-25709	196	59	the	the	DET
fcis-25709	196	60	test	test	NOUN
fcis-25709	196	61	results	result	NOUN
fcis-25709	196	62	of	of	ADP
fcis-25709	196	63	60	60	NUM
fcis-25709	196	64	%	%	NOUN
fcis-25709	196	65	cross	cross	NOUN
fcis-25709	196	66	-	-	NOUN
fcis-25709	196	67	validation	validation	ADJ
fcis-25709	196	68	,	,	PUNCT
fcis-25709	196	69	the	the	DET
fcis-25709	196	70	miou	miou	NOUN
fcis-25709	196	71	of	of	ADP
fcis-25709	196	72	mdnn	mdnn	NOUN
fcis-25709	196	73	is	be	AUX
fcis-25709	196	74	0.4	0.4	NUM
fcis-25709	196	75	%	%	NOUN
fcis-25709	196	76	lower	low	ADJ
fcis-25709	196	77	than	than	ADP
fcis-25709	196	78	that	that	PRON
fcis-25709	196	79	of	of	ADP
fcis-25709	196	80	scf	scf	PROPN
fcis-25709	196	81	-	-	PUNCT
fcis-25709	196	82	net	net	NOUN
fcis-25709	196	83	and	and	CCONJ
fcis-25709	196	84	0.5	0.5	NUM
fcis-25709	196	85	%	%	NOUN
fcis-25709	196	86	lower	low	ADJ
fcis-25709	196	87	than	than	ADP
fcis-25709	196	88	that	that	PRON
fcis-25709	196	89	of	of	ADP
fcis-25709	196	90	baf	baf	PROPN
fcis-25709	196	91	-	-	PUNCT
fcis-25709	196	92	lac	lac	PROPN
fcis-25709	196	93	,	,	PUNCT
fcis-25709	196	94	but	but	CCONJ
fcis-25709	196	95	mdnn	mdnn	NOUN
fcis-25709	196	96	has	have	AUX
fcis-25709	196	97	achieved	achieve	VERB
fcis-25709	196	98	better	well	ADJ
fcis-25709	196	99	performance	performance	NOUN
fcis-25709	196	100	in	in	ADP
fcis-25709	196	101	macc	macc	PROPN
fcis-25709	196	102	and	and	CCONJ
fcis-25709	196	103	oa	oa	INTJ
fcis-25709	196	104	.	.	PUNCT
fcis-25709	196	105	macc	macc	PROPN
fcis-25709	196	106	improved	improve	VERB
fcis-25709	196	107	by	by	ADP
fcis-25709	196	108	7.7	7.7	NUM
fcis-25709	196	109	%	%	NOUN
fcis-25709	196	110	and	and	CCONJ
fcis-25709	196	111	1.9	1.9	NUM
fcis-25709	196	112	%	%	NOUN
fcis-25709	196	113	,	,	PUNCT
fcis-25709	196	114	respectively	respectively	ADV
fcis-25709	196	115	,	,	PUNCT
fcis-25709	196	116	compared	compare	VERB
fcis-25709	196	117	with	with	ADP
fcis-25709	196	118	pointweb	pointweb	ADJ
fcis-25709	196	119	and	and	CCONJ
fcis-25709	196	120	randla	randla	NOUN
fcis-25709	196	121	-	-	PUNCT
fcis-25709	196	122	net	net	NOUN
fcis-25709	196	123	,	,	PUNCT
fcis-25709	196	124	indicating	indicate	VERB
fcis-25709	196	125	that	that	SCONJ
fcis-25709	196	126	the	the	DET
fcis-25709	196	127	proposed	propose	VERB
fcis-25709	196	128	network	network	NOUN
fcis-25709	196	129	has	have	VERB
fcis-25709	196	130	a	a	DET
fcis-25709	196	131	better	well	ADJ
fcis-25709	196	132	segmentation	segmentation	NOUN
fcis-25709	196	133	accuracy	accuracy	NOUN
fcis-25709	196	134	for	for	ADP
fcis-25709	196	135	the	the	DET
fcis-25709	196	136	average	average	ADJ
fcis-25709	196	137	category	category	NOUN
fcis-25709	196	138	in	in	ADP
fcis-25709	196	139	identifying	identify	VERB
fcis-25709	196	140	the	the	DET
fcis-25709	196	141	overall	overall	ADJ
fcis-25709	196	142	structure	structure	NOUN
fcis-25709	196	143	shape	shape	NOUN
fcis-25709	196	144	.	.	PUNCT
fcis-25709	197	1	table	table	NOUN
fcis-25709	197	2	2	2	NUM
fcis-25709	197	3	shows	show	VERB
fcis-25709	197	4	the	the	DET
fcis-25709	197	5	results	result	NOUN
fcis-25709	197	6	of	of	ADP
fcis-25709	197	7	the	the	DET
fcis-25709	197	8	mdnn	mdnn	NOUN
fcis-25709	197	9	's	's	PART
fcis-25709	197	10	quantitative	quantitative	ADJ
fcis-25709	197	11	evaluation	evaluation	NOUN
fcis-25709	197	12	of	of	ADP
fcis-25709	197	13	13	13	NUM
fcis-25709	197	14	category	category	NOUN
fcis-25709	197	15	segmentation	segmentation	NOUN
fcis-25709	197	16	for	for	ADP
fcis-25709	197	17	s3dis	s3dis	PROPN
fcis-25709	197	18	dataset	dataset	ADJ
fcis-25709	197	19	region	region	NOUN
fcis-25709	197	20	5	5	NUM
fcis-25709	197	21	.	.	PUNCT
fcis-25709	198	1	it	it	PRON
fcis-25709	198	2	can	can	AUX
fcis-25709	198	3	be	be	AUX
fcis-25709	198	4	seen	see	VERB
fcis-25709	198	5	that	that	SCONJ
fcis-25709	198	6	mdnn	mdnn	NOUN
fcis-25709	198	7	achieves	achieve	VERB
fcis-25709	198	8	the	the	DET
fcis-25709	198	9	best	good	ADJ
fcis-25709	198	10	performance	performance	NOUN
fcis-25709	198	11	in	in	ADP
fcis-25709	198	12	the	the	DET
fcis-25709	198	13	floor	floor	NOUN
fcis-25709	198	14	,	,	PUNCT
fcis-25709	198	15	window	window	NOUN
fcis-25709	198	16	and	and	CCONJ
fcis-25709	198	17	panel	panel	NOUN
fcis-25709	198	18	categories	category	NOUN
fcis-25709	198	19	,	,	PUNCT
fcis-25709	198	20	improving	improve	VERB
fcis-25709	198	21	by	by	ADP
fcis-25709	198	22	0.2	0.2	NUM
fcis-25709	198	23	%	%	NOUN
fcis-25709	198	24	,	,	PUNCT
fcis-25709	198	25	4.2	4.2	NUM
fcis-25709	198	26	%	%	NOUN
fcis-25709	198	27	and	and	CCONJ
fcis-25709	198	28	1.7	1.7	NUM
fcis-25709	198	29	%	%	NOUN
fcis-25709	198	30	,	,	PUNCT
fcis-25709	198	31	respectively	respectively	ADV
fcis-25709	198	32	,	,	PUNCT
fcis-25709	198	33	compared	compare	VERB
fcis-25709	198	34	with	with	ADP
fcis-25709	198	35	the	the	DET
fcis-25709	198	36	recent	recent	ADJ
fcis-25709	198	37	representative	representative	ADJ
fcis-25709	198	38	network	network	NOUN
fcis-25709	198	39	scf	scf	PROPN
fcis-25709	198	40	-	-	PUNCT
fcis-25709	198	41	net	net	NOUN
fcis-25709	198	42	,	,	PUNCT
fcis-25709	198	43	and	and	CCONJ
fcis-25709	198	44	also	also	ADV
fcis-25709	198	45	achieves	achieve	VERB
fcis-25709	198	46	good	good	ADJ
fcis-25709	198	47	segmentation	segmentation	NOUN
fcis-25709	198	48	accuracy	accuracy	NOUN
fcis-25709	198	49	for	for	ADP
fcis-25709	198	50	objects	object	NOUN
fcis-25709	198	51	such	such	ADJ
fcis-25709	198	52	as	as	ADP
fcis-25709	198	53	roofs	roof	NOUN
fcis-25709	198	54	,	,	PUNCT
fcis-25709	198	55	columns	column	NOUN
fcis-25709	198	56	,	,	PUNCT
fcis-25709	198	57	tables	table	NOUN
fcis-25709	198	58	and	and	CCONJ
fcis-25709	198	59	bookcases	bookcase	NOUN
fcis-25709	198	60	.	.	PUNCT
fcis-25709	199	1	figure	figure	NOUN
fcis-25709	199	2	7	7	NUM
fcis-25709	199	3	visualizes	visualize	VERB
fcis-25709	199	4	some	some	PRON
fcis-25709	199	5	of	of	ADP
fcis-25709	199	6	the	the	DET
fcis-25709	199	7	indoor	indoor	ADJ
fcis-25709	199	8	scenarios	scenario	NOUN
fcis-25709	199	9	17	17	NUM
fcis-25709	199	10	in	in	ADP
fcis-25709	199	11	test	test	NOUN
fcis-25709	199	12	set	set	VERB
fcis-25709	199	13	area	area	NOUN
fcis-25709	199	14	5	5	NUM
fcis-25709	199	15	.	.	PUNCT
fcis-25709	200	1	it	it	PRON
fcis-25709	200	2	can	can	AUX
fcis-25709	200	3	be	be	AUX
fcis-25709	200	4	seen	see	VERB
fcis-25709	200	5	from	from	ADP
fcis-25709	200	6	the	the	DET
fcis-25709	200	7	visualization	visualization	NOUN
fcis-25709	200	8	results	result	NOUN
fcis-25709	200	9	that	that	PRON
fcis-25709	200	10	mdnn	mdnn	NOUN
fcis-25709	200	11	is	be	AUX
fcis-25709	200	12	more	more	ADV
fcis-25709	200	13	accurate	accurate	ADJ
fcis-25709	200	14	for	for	ADP
fcis-25709	200	15	the	the	DET
fcis-25709	200	16	point	point	NOUN
fcis-25709	200	17	segmentation	segmentation	NOUN
fcis-25709	200	18	at	at	ADP
fcis-25709	200	19	the	the	DET
fcis-25709	200	20	edge	edge	NOUN
fcis-25709	200	21	of	of	ADP
fcis-25709	200	22	the	the	DET
fcis-25709	200	23	furniture	furniture	NOUN
fcis-25709	200	24	category	category	NOUN
fcis-25709	200	25	,	,	PUNCT
fcis-25709	200	26	thanks	thank	NOUN
fcis-25709	200	27	to	to	ADP
fcis-25709	200	28	mffm	mffm	VERB
fcis-25709	200	29	capturing	capture	VERB
fcis-25709	200	30	the	the	DET
fcis-25709	200	31	local	local	ADJ
fcis-25709	200	32	geometric	geometric	ADJ
fcis-25709	200	33	features	feature	NOUN
fcis-25709	200	34	and	and	CCONJ
fcis-25709	200	35	high	high	ADJ
fcis-25709	200	36	-	-	PUNCT
fcis-25709	200	37	level	level	NOUN
fcis-25709	200	38	abstract	abstract	ADJ
fcis-25709	200	39	features	feature	NOUN
fcis-25709	200	40	of	of	ADP
fcis-25709	200	41	the	the	DET
fcis-25709	200	42	sampling	sample	VERB
fcis-25709	200	43	points	point	NOUN
fcis-25709	200	44	on	on	ADP
fcis-25709	200	45	a	a	DET
fcis-25709	200	46	multi	multi	ADJ
fcis-25709	200	47	-	-	NOUN
fcis-25709	200	48	scale	scale	NOUN
fcis-25709	200	49	,	,	PUNCT
fcis-25709	200	50	reducing	reduce	VERB
fcis-25709	200	51	the	the	DET
fcis-25709	200	52	feature	feature	NOUN
fcis-25709	200	53	difference	difference	NOUN
fcis-25709	200	54	between	between	ADP
fcis-25709	200	55	the	the	DET
fcis-25709	200	56	same	same	ADJ
fcis-25709	200	57	category	category	NOUN
fcis-25709	200	58	.	.	PUNCT
fcis-25709	201	1	compared	compare	VERB
fcis-25709	201	2	with	with	ADP
fcis-25709	201	3	the	the	DET
fcis-25709	201	4	segmentation	segmentation	NOUN
fcis-25709	201	5	results	result	NOUN
fcis-25709	201	6	of	of	ADP
fcis-25709	201	7	randla	randla	NOUN
fcis-25709	201	8	-	-	PUNCT
fcis-25709	201	9	net	net	NOUN
fcis-25709	201	10	,	,	PUNCT
fcis-25709	201	11	mdnn	mdnn	NOUN
fcis-25709	201	12	achieves	achieve	VERB
fcis-25709	201	13	a	a	DET
fcis-25709	201	14	more	more	ADV
fcis-25709	201	15	complete	complete	ADJ
fcis-25709	201	16	and	and	CCONJ
fcis-25709	201	17	smooth	smooth	ADJ
fcis-25709	201	18	segmentation	segmentation	NOUN
fcis-25709	201	19	for	for	ADP
fcis-25709	201	20	the	the	DET
fcis-25709	201	21	categories	category	NOUN
fcis-25709	201	22	of	of	ADP
fcis-25709	201	23	objects	object	NOUN
fcis-25709	201	24	such	such	ADJ
fcis-25709	201	25	as	as	ADP
fcis-25709	201	26	walls	wall	NOUN
fcis-25709	201	27	,	,	PUNCT
fcis-25709	201	28	boards	board	NOUN
fcis-25709	201	29	,	,	PUNCT
fcis-25709	201	30	and	and	CCONJ
fcis-25709	201	31	debris	debris	NOUN
fcis-25709	201	32	,	,	PUNCT
fcis-25709	201	33	which	which	PRON
fcis-25709	201	34	is	be	AUX
fcis-25709	201	35	due	due	ADJ
fcis-25709	201	36	to	to	ADP
fcis-25709	201	37	the	the	DET
fcis-25709	201	38	stacked	stack	VERB
fcis-25709	201	39	feature	feature	NOUN
fcis-25709	201	40	graph	graph	NOUN
fcis-25709	201	41	convolution	convolution	NOUN
fcis-25709	201	42	operator	operator	NOUN
fcis-25709	201	43	(	(	PUNCT
fcis-25709	201	44	fgco	fgco	NOUN
fcis-25709	201	45	)	)	PUNCT
fcis-25709	201	46	and	and	CCONJ
fcis-25709	201	47	attention	attention	NOUN
fcis-25709	201	48	pooling	pool	VERB
fcis-25709	201	49	layer	layer	NOUN
fcis-25709	201	50	(	(	PUNCT
fcis-25709	201	51	apl	apl	PROPN
fcis-25709	201	52	)	)	PUNCT
fcis-25709	201	53	in	in	ADP
fcis-25709	201	54	the	the	DET
fcis-25709	201	55	local	local	ADJ
fcis-25709	201	56	feature	feature	NOUN
fcis-25709	201	57	aggregation	aggregation	NOUN
fcis-25709	201	58	unit	unit	NOUN
fcis-25709	201	59	,	,	PUNCT
fcis-25709	201	60	which	which	PRON
fcis-25709	201	61	retain	retain	VERB
fcis-25709	201	62	the	the	DET
fcis-25709	201	63	overall	overall	ADJ
fcis-25709	201	64	morphological	morphological	ADJ
fcis-25709	201	65	information	information	NOUN
fcis-25709	201	66	through	through	ADP
fcis-25709	201	67	the	the	DET
fcis-25709	201	68	relative	relative	ADJ
fcis-25709	201	69	position	position	NOUN
fcis-25709	201	70	encoded	encode	VERB
fcis-25709	201	71	features	feature	NOUN
fcis-25709	201	72	.	.	PUNCT
fcis-25709	202	1	expand	expand	VERB
fcis-25709	202	2	the	the	DET
fcis-25709	202	3	receptive	receptive	ADJ
fcis-25709	202	4	domain	domain	NOUN
fcis-25709	202	5	to	to	PART
fcis-25709	202	6	capture	capture	VERB
fcis-25709	202	7	fine	fine	ADJ
fcis-25709	202	8	local	local	ADJ
fcis-25709	202	9	features	feature	NOUN
fcis-25709	202	10	,	,	PUNCT
fcis-25709	202	11	so	so	SCONJ
fcis-25709	202	12	as	as	SCONJ
fcis-25709	202	13	to	to	PART
fcis-25709	202	14	capture	capture	VERB
fcis-25709	202	15	the	the	DET
fcis-25709	202	16	complete	complete	ADJ
fcis-25709	202	17	structural	structural	ADJ
fcis-25709	202	18	features	feature	NOUN
fcis-25709	202	19	of	of	ADP
fcis-25709	202	20	objects	object	NOUN
fcis-25709	202	21	in	in	ADP
fcis-25709	202	22	complex	complex	ADJ
fcis-25709	202	23	scenes	scene	NOUN
fcis-25709	202	24	.	.	PUNCT
fcis-25709	203	1	a.	a.	NOUN
fcis-25709	203	2	primary	primary	PROPN
fcis-25709	203	3	point	point	PROPN
fcis-25709	203	4	cloud	cloud	PROPN
fcis-25709	203	5	b.	b.	PROPN
fcis-25709	203	6	groundtruth	groundtruth	PROPN
fcis-25709	203	7	c.	c.	PROPN
fcis-25709	203	8	pointnet++	pointnet++	PROPN
fcis-25709	203	9	d.	d.	PROPN
fcis-25709	203	10	randla	randla	PROPN
fcis-25709	203	11	-	-	PUNCT
fcis-25709	203	12	net	net	NOUN
fcis-25709	203	13	e.	e.	PROPN
fcis-25709	203	14	mdnn	mdnn	PROPN
fcis-25709	203	15	fig	fig	PROPN
fcis-25709	203	16	7	7	NUM
fcis-25709	203	17	.	.	PUNCT
fcis-25709	204	1	visualization	visualization	NOUN
fcis-25709	204	2	of	of	ADP
fcis-25709	204	3	semantic	semantic	ADJ
fcis-25709	204	4	segmentation	segmentation	NOUN
fcis-25709	204	5	results	result	NOUN
fcis-25709	204	6	of	of	ADP
fcis-25709	204	7	s3dis	s3di	NOUN
fcis-25709	204	8	dataset	dataset	VERB
fcis-25709	204	9	3.4	3.4	NUM
fcis-25709	204	10	.	.	PUNCT
fcis-25709	204	11	ablation	ablation	NOUN
fcis-25709	204	12	experiment	experiment	NOUN
fcis-25709	204	13	in	in	ADP
fcis-25709	204	14	order	order	NOUN
fcis-25709	204	15	to	to	PART
fcis-25709	204	16	further	far	ADV
fcis-25709	204	17	verify	verify	VERB
fcis-25709	204	18	the	the	DET
fcis-25709	204	19	effectiveness	effectiveness	NOUN
fcis-25709	204	20	of	of	ADP
fcis-25709	204	21	each	each	DET
fcis-25709	204	22	module	module	NOUN
fcis-25709	204	23	in	in	ADP
fcis-25709	204	24	the	the	DET
fcis-25709	204	25	mdnn	mdnn	NOUN
fcis-25709	204	26	network	network	NOUN
fcis-25709	204	27	and	and	CCONJ
fcis-25709	204	28	check	check	VERB
fcis-25709	204	29	the	the	DET
fcis-25709	204	30	details	detail	NOUN
fcis-25709	204	31	of	of	ADP
fcis-25709	204	32	each	each	DET
fcis-25709	204	33	part	part	NOUN
fcis-25709	204	34	of	of	ADP
fcis-25709	204	35	the	the	DET
fcis-25709	204	36	network	network	NOUN
fcis-25709	204	37	,	,	PUNCT
fcis-25709	204	38	five	five	NUM
fcis-25709	204	39	ablation	ablation	NOUN
fcis-25709	204	40	experiments	experiment	NOUN
fcis-25709	204	41	were	be	AUX
fcis-25709	204	42	designed	design	VERB
fcis-25709	204	43	on	on	ADP
fcis-25709	204	44	s3dis	s3dis	PROPN
fcis-25709	204	45	region	region	NOUN
fcis-25709	204	46	5	5	NUM
fcis-25709	204	47	using	use	VERB
fcis-25709	204	48	the	the	DET
fcis-25709	204	49	mean	mean	ADJ
fcis-25709	204	50	intersection	intersection	NOUN
fcis-25709	204	51	ratio	ratio	NOUN
fcis-25709	204	52	(	(	PUNCT
fcis-25709	204	53	miou	miou	NOUN
fcis-25709	204	54	)	)	PUNCT
fcis-25709	204	55	as	as	ADP
fcis-25709	204	56	an	an	DET
fcis-25709	204	57	evaluation	evaluation	NOUN
fcis-25709	204	58	index	index	NOUN
fcis-25709	204	59	,	,	PUNCT
fcis-25709	204	60	and	and	CCONJ
fcis-25709	204	61	the	the	DET
fcis-25709	204	62	results	result	NOUN
fcis-25709	204	63	were	be	AUX
fcis-25709	204	64	shown	show	VERB
fcis-25709	204	65	in	in	ADP
fcis-25709	204	66	table	table	NOUN
fcis-25709	204	67	3	3	NUM
fcis-25709	204	68	.	.	PUNCT
fcis-25709	204	69	table	table	NOUN
fcis-25709	204	70	3	3	NUM
fcis-25709	204	71	.	.	X
fcis-25709	204	72	mdnn	mdnn	PROPN
fcis-25709	204	73	network	network	NOUN
fcis-25709	204	74	model	model	NOUN
fcis-25709	204	75	ablation	ablation	NOUN
fcis-25709	204	76	experiment	experiment	NOUN
fcis-25709	204	77	model	model	NOUN
fcis-25709	204	78	dense	dense	ADJ
fcis-25709	204	79	nested	nested	ADJ
fcis-25709	204	80	network	network	NOUN
fcis-25709	204	81	local	local	ADJ
fcis-25709	204	82	feature	feature	NOUN
fcis-25709	204	83	aggregation	aggregation	NOUN
fcis-25709	204	84	unit	unit	NOUN
fcis-25709	204	85	cross	cross	ADJ
fcis-25709	204	86	-	-	ADJ
fcis-25709	204	87	layer	layer	ADJ
fcis-25709	204	88	multi	multi	ADJ
fcis-25709	204	89	-	-	ADJ
fcis-25709	204	90	loss	loss	ADJ
fcis-25709	204	91	monitoring	monitoring	NOUN
fcis-25709	204	92	module	module	NOUN
fcis-25709	204	93	miou(%	miou(%	NOUN
fcis-25709	204	94	)	)	PUNCT
fcis-25709	204	95	(	(	PUNCT
fcis-25709	204	96	a	a	X
fcis-25709	204	97	)	)	PUNCT
fcis-25709	204	98	　 	　 	SPACE
fcis-25709	204	99	65.8	65.8	NUM
fcis-25709	204	100	(	(	PUNCT
fcis-25709	204	101	b	b	NOUN
fcis-25709	204	102	)	)	PUNCT
fcis-25709	204	103	　 　 	　 　 	SPACE
fcis-25709	204	104	67.4	67.4	NUM
fcis-25709	204	105	(	(	PUNCT
fcis-25709	204	106	c	c	NOUN
fcis-25709	204	107	)	)	PUNCT
fcis-25709	204	108	　 　 	　 　 	SPACE
fcis-25709	204	109	67.9	67.9	NUM
fcis-25709	204	110	(	(	PUNCT
fcis-25709	204	111	d	d	X
fcis-25709	204	112	)	)	PUNCT
fcis-25709	204	113	　 　 　 	　 　 　 	SPACE
fcis-25709	204	114	71.2	71.2	NUM
fcis-25709	204	115	in	in	ADP
fcis-25709	204	116	model	model	NOUN
fcis-25709	204	117	(	(	PUNCT
fcis-25709	204	118	a	a	NOUN
fcis-25709	204	119	)	)	PUNCT
fcis-25709	204	120	,	,	PUNCT
fcis-25709	204	121	the	the	DET
fcis-25709	204	122	advantages	advantage	NOUN
fcis-25709	204	123	of	of	ADP
fcis-25709	204	124	cross	cross	ADJ
fcis-25709	204	125	-	-	ADJ
fcis-25709	204	126	scale	scale	ADJ
fcis-25709	204	127	information	information	NOUN
fcis-25709	204	128	interaction	interaction	NOUN
fcis-25709	204	129	of	of	ADP
fcis-25709	204	130	dense	dense	ADJ
fcis-25709	204	131	nested	nested	ADJ
fcis-25709	204	132	network	network	NOUN
fcis-25709	204	133	architecture	architecture	NOUN
fcis-25709	204	134	are	be	AUX
fcis-25709	204	135	evaluated	evaluate	VERB
fcis-25709	204	136	,	,	PUNCT
fcis-25709	204	137	and	and	CCONJ
fcis-25709	204	138	the	the	DET
fcis-25709	204	139	original	original	ADJ
fcis-25709	204	140	u	u	NOUN
fcis-25709	204	141	-	-	ADJ
fcis-25709	204	142	shaped	shape	VERB
fcis-25709	204	143	architecture	architecture	NOUN
fcis-25709	204	144	is	be	AUX
fcis-25709	204	145	used	use	VERB
fcis-25709	204	146	to	to	PART
fcis-25709	204	147	replace	replace	VERB
fcis-25709	204	148	the	the	DET
fcis-25709	204	149	dense	dense	ADJ
fcis-25709	204	150	nested	nested	ADJ
fcis-25709	204	151	network	network	NOUN
fcis-25709	204	152	architecture	architecture	NOUN
fcis-25709	204	153	.	.	PUNCT
fcis-25709	205	1	compared	compare	VERB
fcis-25709	205	2	with	with	ADP
fcis-25709	205	3	model	model	NOUN
fcis-25709	205	4	(	(	PUNCT
fcis-25709	205	5	a	a	NOUN
fcis-25709	205	6	)	)	PUNCT
fcis-25709	205	7	,	,	PUNCT
fcis-25709	205	8	the	the	DET
fcis-25709	205	9	miou	miou	NOUN
fcis-25709	205	10	of	of	ADP
fcis-25709	205	11	model	model	NOUN
fcis-25709	205	12	(	(	PUNCT
fcis-25709	205	13	d	d	NOUN
fcis-25709	205	14	)	)	PUNCT
fcis-25709	205	15	is	be	AUX
fcis-25709	205	16	significantly	significantly	ADV
fcis-25709	205	17	increased	increase	VERB
fcis-25709	205	18	by	by	ADP
fcis-25709	205	19	5.4	5.4	NUM
fcis-25709	205	20	%	%	NOUN
fcis-25709	205	21	,	,	PUNCT
fcis-25709	205	22	indicating	indicate	VERB
fcis-25709	205	23	that	that	SCONJ
fcis-25709	205	24	the	the	DET
fcis-25709	205	25	dense	dense	ADJ
fcis-25709	205	26	nested	nested	ADJ
fcis-25709	205	27	network	network	NOUN
fcis-25709	205	28	architecture	architecture	NOUN
fcis-25709	205	29	has	have	VERB
fcis-25709	205	30	the	the	DET
fcis-25709	205	31	greatest	great	ADJ
fcis-25709	205	32	impact	impact	NOUN
fcis-25709	205	33	on	on	ADP
fcis-25709	205	34	network	network	NOUN
fcis-25709	205	35	performance	performance	NOUN
fcis-25709	205	36	.	.	PUNCT
fcis-25709	206	1	the	the	DET
fcis-25709	206	2	reason	reason	NOUN
fcis-25709	206	3	is	be	AUX
fcis-25709	206	4	that	that	SCONJ
fcis-25709	206	5	the	the	DET
fcis-25709	206	6	dense	dense	ADJ
fcis-25709	206	7	nested	nested	ADJ
fcis-25709	206	8	network	network	NOUN
fcis-25709	206	9	architecture	architecture	NOUN
fcis-25709	206	10	is	be	AUX
fcis-25709	206	11	more	more	ADV
fcis-25709	206	12	conducive	conducive	ADJ
fcis-25709	206	13	to	to	ADP
fcis-25709	206	14	the	the	DET
fcis-25709	206	15	integration	integration	NOUN
fcis-25709	206	16	of	of	ADP
fcis-25709	206	17	rich	rich	ADJ
fcis-25709	206	18	geometric	geometric	ADJ
fcis-25709	206	19	information	information	NOUN
fcis-25709	206	20	and	and	CCONJ
fcis-25709	206	21	abstract	abstract	ADJ
fcis-25709	206	22	semantic	semantic	ADJ
fcis-25709	206	23	information	information	NOUN
fcis-25709	206	24	,	,	PUNCT
fcis-25709	206	25	and	and	CCONJ
fcis-25709	206	26	enhance	enhance	VERB
fcis-25709	206	27	the	the	DET
fcis-25709	206	28	ability	ability	NOUN
fcis-25709	206	29	of	of	ADP
fcis-25709	206	30	cross	cross	ADJ
fcis-25709	206	31	-	-	ADJ
fcis-25709	206	32	scale	scale	ADJ
fcis-25709	206	33	information	information	NOUN
fcis-25709	206	34	transmission	transmission	NOUN
fcis-25709	206	35	.	.	PUNCT
fcis-25709	207	1	model	model	NOUN
fcis-25709	207	2	(	(	PUNCT
fcis-25709	207	3	b	b	NOUN
fcis-25709	207	4	)	)	PUNCT
fcis-25709	207	5	evaluated	evaluate	VERB
fcis-25709	207	6	the	the	DET
fcis-25709	207	7	effect	effect	NOUN
fcis-25709	207	8	of	of	ADP
fcis-25709	207	9	local	local	ADJ
fcis-25709	207	10	feature	feature	NOUN
fcis-25709	207	11	aggregation	aggregation	NOUN
fcis-25709	207	12	units	unit	NOUN
fcis-25709	207	13	on	on	ADP
fcis-25709	207	14	segmentation	segmentation	NOUN
fcis-25709	207	15	accuracy	accuracy	NOUN
fcis-25709	207	16	.	.	PUNCT
fcis-25709	208	1	replace	replace	VERB
fcis-25709	208	2	the	the	DET
fcis-25709	208	3	local	local	ADJ
fcis-25709	208	4	feature	feature	NOUN
fcis-25709	208	5	aggregation	aggregation	NOUN
fcis-25709	208	6	unit	unit	NOUN
fcis-25709	208	7	with	with	ADP
fcis-25709	208	8	the	the	DET
fcis-25709	208	9	feature	feature	NOUN
fcis-25709	208	10	aggregation	aggregation	NOUN
fcis-25709	208	11	module	module	NOUN
fcis-25709	208	12	in	in	ADP
fcis-25709	208	13	randla	randla	NOUN
fcis-25709	208	14	-	-	PUNCT
fcis-25709	208	15	net	net	NOUN
fcis-25709	208	16	[	[	X
fcis-25709	208	17	12	12	NUM
fcis-25709	208	18	]	]	PUNCT
fcis-25709	208	19	.	.	PUNCT
fcis-25709	209	1	it	it	PRON
fcis-25709	209	2	can	can	AUX
fcis-25709	209	3	be	be	AUX
fcis-25709	209	4	seen	see	VERB
fcis-25709	209	5	that	that	SCONJ
fcis-25709	209	6	the	the	DET
fcis-25709	209	7	miou	miou	NOUN
fcis-25709	209	8	of	of	ADP
fcis-25709	209	9	model	model	NOUN
fcis-25709	209	10	(	(	PUNCT
fcis-25709	209	11	d	d	X
fcis-25709	209	12	)	)	PUNCT
fcis-25709	209	13	is	be	AUX
fcis-25709	209	14	3.8	3.8	NUM
fcis-25709	209	15	%	%	NOUN
fcis-25709	209	16	higher	high	ADJ
fcis-25709	209	17	than	than	ADP
fcis-25709	209	18	that	that	PRON
fcis-25709	209	19	of	of	ADP
fcis-25709	209	20	model	model	NOUN
fcis-25709	209	21	(	(	PUNCT
fcis-25709	209	22	b	b	NOUN
fcis-25709	209	23	)	)	PUNCT
fcis-25709	209	24	,	,	PUNCT
fcis-25709	209	25	indicating	indicate	VERB
fcis-25709	209	26	that	that	SCONJ
fcis-25709	209	27	this	this	DET
fcis-25709	209	28	unit	unit	NOUN
fcis-25709	209	29	can	can	AUX
fcis-25709	209	30	effectively	effectively	ADV
fcis-25709	209	31	extend	extend	VERB
fcis-25709	209	32	the	the	DET
fcis-25709	209	33	perception	perception	NOUN
fcis-25709	209	34	range	range	NOUN
fcis-25709	209	35	of	of	ADP
fcis-25709	209	36	local	local	ADJ
fcis-25709	209	37	neighborhoods	neighborhood	NOUN
fcis-25709	209	38	,	,	PUNCT
fcis-25709	209	39	capture	capture	VERB
fcis-25709	209	40	local	local	ADJ
fcis-25709	209	41	spatial	spatial	ADJ
fcis-25709	209	42	details	detail	NOUN
fcis-25709	209	43	and	and	CCONJ
fcis-25709	209	44	semantic	semantic	ADJ
fcis-25709	209	45	information	information	NOUN
fcis-25709	209	46	in	in	ADP
fcis-25709	209	47	different	different	ADJ
fcis-25709	209	48	receptive	receptive	ADJ
fcis-25709	209	49	fields	field	NOUN
fcis-25709	209	50	,	,	PUNCT
fcis-25709	209	51	and	and	CCONJ
fcis-25709	209	52	thus	thus	ADV
fcis-25709	209	53	enhance	enhance	VERB
fcis-25709	209	54	the	the	DET
fcis-25709	209	55	feature	feature	NOUN
fcis-25709	209	56	information	information	NOUN
fcis-25709	209	57	of	of	ADP
fcis-25709	209	58	each	each	DET
fcis-25709	209	59	point	point	NOUN
fcis-25709	209	60	.	.	PUNCT
fcis-25709	210	1	model	model	NOUN
fcis-25709	210	2	(	(	PUNCT
fcis-25709	210	3	c	c	NOUN
fcis-25709	210	4	)	)	PUNCT
fcis-25709	210	5	18	18	NUM
fcis-25709	210	6	verifies	verifie	NOUN
fcis-25709	210	7	the	the	DET
fcis-25709	210	8	effectiveness	effectiveness	NOUN
fcis-25709	210	9	of	of	ADP
fcis-25709	210	10	the	the	DET
fcis-25709	210	11	cross	cross	ADJ
fcis-25709	210	12	-	-	ADJ
fcis-25709	210	13	layer	layer	ADJ
fcis-25709	210	14	multi	multi	ADJ
fcis-25709	210	15	-	-	ADJ
fcis-25709	210	16	loss	loss	ADJ
fcis-25709	210	17	monitoring	monitoring	NOUN
fcis-25709	210	18	module	module	NOUN
fcis-25709	210	19	.	.	PUNCT
fcis-25709	211	1	the	the	DET
fcis-25709	211	2	results	result	NOUN
fcis-25709	211	3	show	show	VERB
fcis-25709	211	4	that	that	SCONJ
fcis-25709	211	5	the	the	DET
fcis-25709	211	6	accuracy	accuracy	NOUN
fcis-25709	211	7	of	of	ADP
fcis-25709	211	8	miou	miou	NOUN
fcis-25709	211	9	can	can	AUX
fcis-25709	211	10	be	be	AUX
fcis-25709	211	11	improved	improve	VERB
fcis-25709	211	12	by	by	ADP
fcis-25709	211	13	3.3	3.3	NUM
fcis-25709	211	14	%	%	NOUN
fcis-25709	211	15	after	after	ADP
fcis-25709	211	16	adding	add	VERB
fcis-25709	211	17	the	the	DET
fcis-25709	211	18	cross	cross	ADJ
fcis-25709	211	19	-	-	ADJ
fcis-25709	211	20	layer	layer	ADJ
fcis-25709	211	21	multi	multi	ADJ
fcis-25709	211	22	-	-	ADJ
fcis-25709	211	23	loss	loss	ADJ
fcis-25709	211	24	monitoring	monitoring	NOUN
fcis-25709	211	25	module	module	NOUN
fcis-25709	211	26	.	.	PUNCT
fcis-25709	212	1	this	this	PRON
fcis-25709	212	2	is	be	AUX
fcis-25709	212	3	because	because	SCONJ
fcis-25709	212	4	when	when	SCONJ
fcis-25709	212	5	the	the	DET
fcis-25709	212	6	cross	cross	ADJ
fcis-25709	212	7	-	-	ADJ
fcis-25709	212	8	layer	layer	ADJ
fcis-25709	212	9	multi	multi	ADJ
fcis-25709	212	10	-	-	ADJ
fcis-25709	212	11	loss	loss	ADJ
fcis-25709	212	12	monitoring	monitoring	NOUN
fcis-25709	212	13	module	module	NOUN
fcis-25709	212	14	is	be	AUX
fcis-25709	212	15	deleted	delete	VERB
fcis-25709	212	16	,	,	PUNCT
fcis-25709	212	17	the	the	DET
fcis-25709	212	18	whole	whole	ADJ
fcis-25709	212	19	network	network	NOUN
fcis-25709	212	20	is	be	AUX
fcis-25709	212	21	limited	limit	VERB
fcis-25709	212	22	to	to	ADP
fcis-25709	212	23	the	the	DET
fcis-25709	212	24	deepest	deep	ADJ
fcis-25709	212	25	nested	nested	ADJ
fcis-25709	212	26	block	block	NOUN
fcis-25709	212	27	to	to	ADP
fcis-25709	212	28	output	output	NOUN
fcis-25709	212	29	losses	loss	NOUN
fcis-25709	212	30	,	,	PUNCT
fcis-25709	212	31	and	and	CCONJ
fcis-25709	212	32	the	the	DET
fcis-25709	212	33	training	training	NOUN
fcis-25709	212	34	process	process	NOUN
fcis-25709	212	35	fails	fail	VERB
fcis-25709	212	36	to	to	PART
fcis-25709	212	37	use	use	VERB
fcis-25709	212	38	the	the	DET
fcis-25709	212	39	multi	multi	ADJ
fcis-25709	212	40	-	-	ADJ
fcis-25709	212	41	depth	depth	ADJ
fcis-25709	212	42	output	output	NOUN
fcis-25709	212	43	prediction	prediction	NOUN
fcis-25709	212	44	to	to	PART
fcis-25709	212	45	enhance	enhance	VERB
fcis-25709	212	46	the	the	DET
fcis-25709	212	47	output	output	NOUN
fcis-25709	212	48	results	result	NOUN
fcis-25709	212	49	.	.	PUNCT
fcis-25709	213	1	model	model	NOUN
fcis-25709	213	2	(	(	PUNCT
fcis-25709	213	3	d	d	X
fcis-25709	213	4	)	)	PUNCT
fcis-25709	213	5	is	be	AUX
fcis-25709	213	6	the	the	DET
fcis-25709	213	7	complete	complete	ADJ
fcis-25709	213	8	network	network	NOUN
fcis-25709	213	9	architecture	architecture	NOUN
fcis-25709	213	10	proposed	propose	VERB
fcis-25709	213	11	in	in	ADP
fcis-25709	213	12	this	this	DET
fcis-25709	213	13	paper	paper	NOUN
fcis-25709	213	14	,	,	PUNCT
fcis-25709	213	15	which	which	PRON
fcis-25709	213	16	shows	show	VERB
fcis-25709	213	17	that	that	SCONJ
fcis-25709	213	18	each	each	DET
fcis-25709	213	19	module	module	NOUN
fcis-25709	213	20	can	can	AUX
fcis-25709	213	21	achieve	achieve	VERB
fcis-25709	213	22	the	the	DET
fcis-25709	213	23	best	good	ADJ
fcis-25709	213	24	performance	performance	NOUN
fcis-25709	213	25	by	by	ADP
fcis-25709	213	26	complementing	complement	VERB
fcis-25709	213	27	each	each	DET
fcis-25709	213	28	other	other	ADJ
fcis-25709	213	29	.	.	PUNCT
fcis-25709	214	1	4	4	X
fcis-25709	214	2	.	.	X
fcis-25709	214	3	summary	summary	NOUN
fcis-25709	214	4	in	in	ADP
fcis-25709	214	5	this	this	DET
fcis-25709	214	6	paper	paper	NOUN
fcis-25709	214	7	,	,	PUNCT
fcis-25709	214	8	a	a	DET
fcis-25709	214	9	multi	multi	ADJ
fcis-25709	214	10	-	-	ADJ
fcis-25709	214	11	scale	scale	ADJ
fcis-25709	214	12	dense	dense	ADJ
fcis-25709	214	13	nested	nested	ADJ
fcis-25709	214	14	network	network	NOUN
fcis-25709	214	15	mdnn	mdnn	NOUN
fcis-25709	214	16	is	be	AUX
fcis-25709	214	17	proposed	propose	VERB
fcis-25709	214	18	for	for	ADP
fcis-25709	214	19	3d	3d	NUM
fcis-25709	214	20	point	point	NOUN
fcis-25709	214	21	cloud	cloud	ADJ
fcis-25709	214	22	semantic	semantic	ADJ
fcis-25709	214	23	segmentation	segmentation	NOUN
fcis-25709	214	24	.	.	PUNCT
fcis-25709	215	1	through	through	ADP
fcis-25709	215	2	the	the	DET
fcis-25709	215	3	improved	improve	VERB
fcis-25709	215	4	dense	dense	ADJ
fcis-25709	215	5	nested	nested	ADJ
fcis-25709	215	6	network	network	NOUN
fcis-25709	215	7	architecture	architecture	NOUN
fcis-25709	215	8	,	,	PUNCT
fcis-25709	215	9	the	the	DET
fcis-25709	215	10	crosslayer	crosslayer	NOUN
fcis-25709	215	11	flow	flow	NOUN
fcis-25709	215	12	of	of	ADP
fcis-25709	215	13	multi	multi	ADJ
fcis-25709	215	14	-	-	ADJ
fcis-25709	215	15	scale	scale	ADJ
fcis-25709	215	16	features	feature	NOUN
fcis-25709	215	17	is	be	AUX
fcis-25709	215	18	realized	realize	VERB
fcis-25709	215	19	by	by	ADP
fcis-25709	215	20	adding	add	VERB
fcis-25709	215	21	dense	dense	ADJ
fcis-25709	215	22	jump	jump	NOUN
fcis-25709	215	23	connections	connection	NOUN
fcis-25709	215	24	in	in	ADP
fcis-25709	215	25	horizontal	horizontal	ADJ
fcis-25709	215	26	and	and	CCONJ
fcis-25709	215	27	vertical	vertical	ADJ
fcis-25709	215	28	directions	direction	NOUN
fcis-25709	215	29	.	.	PUNCT
fcis-25709	216	1	in	in	ADP
fcis-25709	216	2	addition	addition	NOUN
fcis-25709	216	3	,	,	PUNCT
fcis-25709	216	4	a	a	DET
fcis-25709	216	5	local	local	ADJ
fcis-25709	216	6	feature	feature	NOUN
fcis-25709	216	7	aggregation	aggregation	NOUN
fcis-25709	216	8	unit	unit	NOUN
fcis-25709	216	9	is	be	AUX
fcis-25709	216	10	designed	design	VERB
fcis-25709	216	11	in	in	ADP
fcis-25709	216	12	the	the	DET
fcis-25709	216	13	multi	multi	ADJ
fcis-25709	216	14	-	-	ADJ
fcis-25709	216	15	scale	scale	ADJ
fcis-25709	216	16	feature	feature	NOUN
fcis-25709	216	17	fusion	fusion	NOUN
fcis-25709	216	18	module	module	NOUN
fcis-25709	216	19	,	,	PUNCT
fcis-25709	216	20	which	which	PRON
fcis-25709	216	21	enlarges	enlarge	VERB
fcis-25709	216	22	the	the	DET
fcis-25709	216	23	receptive	receptive	ADJ
fcis-25709	216	24	domain	domain	NOUN
fcis-25709	216	25	through	through	ADP
fcis-25709	216	26	feature	feature	NOUN
fcis-25709	216	27	propagation	propagation	NOUN
fcis-25709	216	28	and	and	CCONJ
fcis-25709	216	29	expands	expand	VERB
fcis-25709	216	30	the	the	DET
fcis-25709	216	31	ability	ability	NOUN
fcis-25709	216	32	of	of	ADP
fcis-25709	216	33	the	the	DET
fcis-25709	216	34	model	model	NOUN
fcis-25709	216	35	to	to	PART
fcis-25709	216	36	capture	capture	VERB
fcis-25709	216	37	local	local	ADJ
fcis-25709	216	38	features	feature	NOUN
fcis-25709	216	39	at	at	ADP
fcis-25709	216	40	different	different	ADJ
fcis-25709	216	41	depths	depth	NOUN
fcis-25709	216	42	.	.	PUNCT
fcis-25709	217	1	at	at	ADP
fcis-25709	217	2	the	the	DET
fcis-25709	217	3	same	same	ADJ
fcis-25709	217	4	time	time	NOUN
fcis-25709	217	5	,	,	PUNCT
fcis-25709	217	6	the	the	DET
fcis-25709	217	7	cross	cross	ADJ
fcis-25709	217	8	-	-	ADJ
fcis-25709	217	9	layer	layer	ADJ
fcis-25709	217	10	multi	multi	ADJ
fcis-25709	217	11	-	-	ADJ
fcis-25709	217	12	loss	loss	ADJ
fcis-25709	217	13	monitoring	monitoring	NOUN
fcis-25709	217	14	module	module	NOUN
fcis-25709	217	15	adopted	adopt	VERB
fcis-25709	217	16	in	in	ADP
fcis-25709	217	17	this	this	DET
fcis-25709	217	18	paper	paper	NOUN
fcis-25709	217	19	controls	control	NOUN
fcis-25709	217	20	and	and	CCONJ
fcis-25709	217	21	optimizes	optimize	VERB
fcis-25709	217	22	the	the	DET
fcis-25709	217	23	feature	feature	NOUN
fcis-25709	217	24	learning	learning	NOUN
fcis-25709	217	25	process	process	NOUN
fcis-25709	217	26	,	,	PUNCT
fcis-25709	217	27	which	which	PRON
fcis-25709	217	28	significantly	significantly	ADV
fcis-25709	217	29	improves	improve	VERB
fcis-25709	217	30	the	the	DET
fcis-25709	217	31	multi	multi	ADJ
fcis-25709	217	32	-	-	ADJ
fcis-25709	217	33	scale	scale	ADJ
fcis-25709	217	34	feature	feature	NOUN
fcis-25709	217	35	fusion	fusion	NOUN
fcis-25709	217	36	capability	capability	NOUN
fcis-25709	217	37	and	and	CCONJ
fcis-25709	217	38	the	the	DET
fcis-25709	217	39	stability	stability	NOUN
fcis-25709	217	40	of	of	ADP
fcis-25709	217	41	the	the	DET
fcis-25709	217	42	learning	learning	NOUN
fcis-25709	217	43	process	process	NOUN
fcis-25709	217	44	.	.	PUNCT
fcis-25709	218	1	in	in	ADP
fcis-25709	218	2	this	this	DET
fcis-25709	218	3	paper	paper	NOUN
fcis-25709	218	4	,	,	PUNCT
fcis-25709	218	5	quantitative	quantitative	ADJ
fcis-25709	218	6	experiments	experiment	NOUN
fcis-25709	218	7	are	be	AUX
fcis-25709	218	8	carried	carry	VERB
fcis-25709	218	9	out	out	ADP
fcis-25709	218	10	on	on	ADP
fcis-25709	218	11	the	the	DET
fcis-25709	218	12	s3dis	s3dis	PROPN
fcis-25709	218	13	benchmark	benchmark	NOUN
fcis-25709	218	14	dataset	dataset	NOUN
fcis-25709	218	15	.	.	PUNCT
fcis-25709	219	1	the	the	DET
fcis-25709	219	2	experiments	experiment	NOUN
fcis-25709	219	3	show	show	VERB
fcis-25709	219	4	that	that	SCONJ
fcis-25709	219	5	compared	compare	VERB
fcis-25709	219	6	with	with	ADP
fcis-25709	219	7	randla	randla	NOUN
fcis-25709	219	8	-	-	PUNCT
fcis-25709	219	9	net	net	NOUN
fcis-25709	219	10	network	network	NOUN
fcis-25709	219	11	,	,	PUNCT
fcis-25709	219	12	the	the	DET
fcis-25709	219	13	average	average	ADJ
fcis-25709	219	14	intersection	intersection	NOUN
fcis-25709	219	15	ratio	ratio	NOUN
fcis-25709	219	16	is	be	AUX
fcis-25709	219	17	increased	increase	VERB
fcis-25709	219	18	by	by	ADP
fcis-25709	219	19	1.2	1.2	NUM
fcis-25709	219	20	%	%	NOUN
fcis-25709	219	21	,	,	PUNCT
fcis-25709	219	22	the	the	DET
fcis-25709	219	23	average	average	ADJ
fcis-25709	219	24	accuracy	accuracy	NOUN
fcis-25709	219	25	is	be	AUX
fcis-25709	219	26	increased	increase	VERB
fcis-25709	219	27	by	by	ADP
fcis-25709	219	28	1.9	1.9	NUM
fcis-25709	219	29	%	%	NOUN
fcis-25709	219	30	,	,	PUNCT
fcis-25709	219	31	and	and	CCONJ
fcis-25709	219	32	the	the	DET
fcis-25709	219	33	overall	overall	ADJ
fcis-25709	219	34	accuracy	accuracy	NOUN
fcis-25709	219	35	is	be	AUX
fcis-25709	219	36	increased	increase	VERB
fcis-25709	219	37	by	by	ADP
fcis-25709	219	38	0.7	0.7	NUM
fcis-25709	219	39	%	%	NOUN
fcis-25709	219	40	.	.	PUNCT
fcis-25709	220	1	the	the	DET
fcis-25709	220	2	visual	visual	ADJ
fcis-25709	220	3	comparison	comparison	NOUN
fcis-25709	220	4	results	result	NOUN
fcis-25709	220	5	show	show	VERB
fcis-25709	220	6	that	that	SCONJ
fcis-25709	220	7	mdnn	mdnn	NOUN
fcis-25709	220	8	has	have	VERB
fcis-25709	220	9	higher	high	ADJ
fcis-25709	220	10	segmentation	segmentation	NOUN
fcis-25709	220	11	accuracy	accuracy	NOUN
fcis-25709	220	12	for	for	ADP
fcis-25709	220	13	local	local	ADJ
fcis-25709	220	14	edge	edge	NOUN
fcis-25709	220	15	details	detail	NOUN
fcis-25709	220	16	when	when	SCONJ
fcis-25709	220	17	facing	face	VERB
fcis-25709	220	18	sparse	sparse	ADJ
fcis-25709	220	19	point	point	NOUN
fcis-25709	220	20	clouds	cloud	NOUN
fcis-25709	220	21	.	.	PUNCT
fcis-25709	221	1	the	the	DET
fcis-25709	221	2	ablation	ablation	NOUN
fcis-25709	221	3	research	research	NOUN
fcis-25709	221	4	and	and	CCONJ
fcis-25709	221	5	analysis	analysis	NOUN
fcis-25709	221	6	of	of	ADP
fcis-25709	221	7	different	different	ADJ
fcis-25709	221	8	network	network	NOUN
fcis-25709	221	9	designs	design	NOUN
fcis-25709	221	10	demonstrate	demonstrate	VERB
fcis-25709	221	11	the	the	DET
fcis-25709	221	12	high	high	ADJ
fcis-25709	221	13	performance	performance	NOUN
fcis-25709	221	14	and	and	CCONJ
fcis-25709	221	15	effectiveness	effectiveness	NOUN
fcis-25709	221	16	of	of	ADP
fcis-25709	221	17	each	each	DET
fcis-25709	221	18	module	module	NOUN
fcis-25709	221	19	in	in	ADP
fcis-25709	221	20	the	the	DET
fcis-25709	221	21	network	network	NOUN
fcis-25709	221	22	.	.	PUNCT
fcis-25709	222	1	acknowledgments	acknowledgment	NOUN
fcis-25709	222	2	fund	fund	PROPN
fcis-25709	222	3	project	project	NOUN
fcis-25709	222	4	:	:	PUNCT
fcis-25709	222	5	science	science	NOUN
fcis-25709	222	6	and	and	CCONJ
fcis-25709	222	7	technology	technology	NOUN
fcis-25709	222	8	research	research	NOUN
fcis-25709	222	9	project	project	NOUN
fcis-25709	222	10	of	of	ADP
fcis-25709	222	11	education	education	PROPN
fcis-25709	222	12	department	department	PROPN
fcis-25709	222	13	of	of	ADP
fcis-25709	222	14	jilin	jilin	PROPN
fcis-25709	222	15	province	province	PROPN
fcis-25709	222	16	(	(	PUNCT
fcis-25709	222	17	jjkh20240314kj	jjkh20240314kj	PROPN
fcis-25709	222	18	)	)	PUNCT
fcis-25709	222	19	.	.	PUNCT
fcis-25709	223	1	references	reference	NOUN
fcis-25709	223	2	[	[	X
fcis-25709	223	3	1	1	X
fcis-25709	223	4	]	]	PUNCT
fcis-25709	223	5	wang	wang	PROPN
fcis-25709	223	6	c	c	PROPN
fcis-25709	223	7	,	,	PUNCT
fcis-25709	223	8	pastore	pastore	NOUN
fcis-25709	223	9	f	f	PROPN
fcis-25709	223	10	,	,	PUNCT
fcis-25709	223	11	goknil	goknil	NOUN
fcis-25709	223	12	a	a	NOUN
fcis-25709	223	13	,	,	PUNCT
fcis-25709	223	14	et	et	PROPN
fcis-25709	223	15	al	al	PROPN
fcis-25709	223	16	.	.	PROPN
fcis-25709	223	17	automatic	automatic	ADJ
fcis-25709	223	18	generation	generation	NOUN
fcis-25709	223	19	of	of	ADP
fcis-25709	223	20	acceptance	acceptance	NOUN
fcis-25709	223	21	test	test	NOUN
fcis-25709	223	22	cases	case	NOUN
fcis-25709	223	23	from	from	ADP
fcis-25709	223	24	use	use	NOUN
fcis-25709	223	25	case	case	NOUN
fcis-25709	223	26	specifications	specification	NOUN
fcis-25709	223	27	:	:	PUNCT
fcis-25709	223	28	an	an	DET
fcis-25709	223	29	nlp	nlp	NOUN
fcis-25709	223	30	-	-	PUNCT
fcis-25709	223	31	based	base	VERB
fcis-25709	223	32	approach[j	approach[j	NOUN
fcis-25709	223	33	]	]	PUNCT
fcis-25709	223	34	.	.	PUNCT
fcis-25709	224	1	ieee	ieee	NOUN
fcis-25709	224	2	transactions	transaction	NOUN
fcis-25709	224	3	on	on	ADP
fcis-25709	224	4	software	software	NOUN
fcis-25709	224	5	engineering	engineering	NOUN
fcis-25709	224	6	,	,	PUNCT
fcis-25709	224	7	2020	2020	NUM
fcis-25709	224	8	,	,	PUNCT
fcis-25709	224	9	48(2	48(2	NUM
fcis-25709	224	10	):	):	PUNCT
fcis-25709	224	11	585	585	NUM
fcis-25709	224	12	-	-	SYM
fcis-25709	224	13	616	616	NUM
fcis-25709	224	14	.	.	PUNCT
fcis-25709	225	1	[	[	X
fcis-25709	225	2	2	2	X
fcis-25709	225	3	]	]	PUNCT
fcis-25709	225	4	kolhatkar	kolhatkar	NOUN
fcis-25709	225	5	c	c	X
fcis-25709	225	6	,	,	PUNCT
fcis-25709	225	7	wagle	wagle	PROPN
fcis-25709	225	8	k.	k.	PROPN
fcis-25709	225	9	review	review	PROPN
fcis-25709	225	10	of	of	ADP
fcis-25709	225	11	slam	slam	NOUN
fcis-25709	225	12	algorithms	algorithm	NOUN
fcis-25709	225	13	for	for	ADP
fcis-25709	225	14	indoor	indoor	ADJ
fcis-25709	225	15	mobile	mobile	ADJ
fcis-25709	225	16	robot	robot	NOUN
fcis-25709	225	17	with	with	ADP
fcis-25709	225	18	lidar	lidar	NOUN
fcis-25709	225	19	and	and	CCONJ
fcis-25709	225	20	rgb	rgb	PROPN
fcis-25709	225	21	-	-	PROPN
fcis-25709	225	22	d	d	PROPN
fcis-25709	225	23	camera	camera	NOUN
fcis-25709	225	24	technology[j	technology[j	NOUN
fcis-25709	225	25	]	]	PUNCT
fcis-25709	225	26	.	.	PUNCT
fcis-25709	226	1	innovations	innovation	NOUN
fcis-25709	226	2	in	in	ADP
fcis-25709	226	3	electrical	electrical	ADJ
fcis-25709	226	4	and	and	CCONJ
fcis-25709	226	5	electronic	electronic	ADJ
fcis-25709	226	6	engineering	engineering	NOUN
fcis-25709	226	7	:	:	PUNCT
fcis-25709	226	8	proceedings	proceeding	NOUN
fcis-25709	226	9	of	of	ADP
fcis-25709	226	10	iceee	iceee	NOUN
fcis-25709	226	11	2020	2020	NUM
fcis-25709	226	12	,	,	PUNCT
fcis-25709	226	13	2021	2021	NUM
fcis-25709	226	14	:	:	PUNCT
fcis-25709	226	15	397	397	NUM
fcis-25709	226	16	-	-	SYM
fcis-25709	226	17	409	409	NUM
fcis-25709	226	18	.	.	PUNCT
fcis-25709	227	1	[	[	X
fcis-25709	227	2	3	3	NUM
fcis-25709	227	3	]	]	X
fcis-25709	227	4	zaman	zaman	X
fcis-25709	227	5	f	f	PROPN
fcis-25709	227	6	,	,	PUNCT
fcis-25709	227	7	wong	wong	PROPN
fcis-25709	227	8	y	y	PROPN
fcis-25709	227	9	p	p	PROPN
fcis-25709	227	10	,	,	PUNCT
fcis-25709	227	11	ng	ng	PROPN
fcis-25709	227	12	b	b	PROPN
fcis-25709	227	13	y.	y.	PROPN
fcis-25709	227	14	density	density	PROPN
fcis-25709	227	15	-	-	PUNCT
fcis-25709	227	16	based	base	VERB
fcis-25709	227	17	denoising	denoising	NOUN
fcis-25709	227	18	of	of	ADP
fcis-25709	227	19	point	point	NOUN
fcis-25709	227	20	cloud[c]//9th	cloud[c]//9th	ADJ
fcis-25709	227	21	international	international	ADJ
fcis-25709	227	22	conference	conference	NOUN
fcis-25709	227	23	on	on	ADP
fcis-25709	227	24	robotic	robotic	ADJ
fcis-25709	227	25	,	,	PUNCT
fcis-25709	227	26	vision	vision	NOUN
fcis-25709	227	27	,	,	PUNCT
fcis-25709	227	28	signal	signal	NOUN
fcis-25709	227	29	processing	processing	NOUN
fcis-25709	227	30	and	and	CCONJ
fcis-25709	227	31	power	power	NOUN
fcis-25709	227	32	applications	application	NOUN
fcis-25709	227	33	:	:	PUNCT
fcis-25709	227	34	empowering	empower	VERB
fcis-25709	227	35	research	research	NOUN
fcis-25709	227	36	and	and	CCONJ
fcis-25709	227	37	innovation	innovation	NOUN
fcis-25709	227	38	.	.	PUNCT
fcis-25709	228	1	springer	springer	PROPN
fcis-25709	228	2	singapore	singapore	PROPN
fcis-25709	228	3	,	,	PUNCT
fcis-25709	228	4	2017	2017	NUM
fcis-25709	228	5	:	:	PUNCT
fcis-25709	228	6	287	287	NUM
fcis-25709	228	7	-	-	SYM
fcis-25709	228	8	295	295	NUM
fcis-25709	228	9	.	.	PUNCT
fcis-25709	229	1	[	[	X
fcis-25709	229	2	4	4	X
fcis-25709	229	3	]	]	X
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fcis-25709	229	5	p	p	NOUN
fcis-25709	229	6	,	,	PUNCT
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fcis-25709	229	8	v	v	PROPN
fcis-25709	229	9	b.	b.	PROPN
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fcis-25709	229	11	3d	3d	PROPN
fcis-25709	229	12	point	point	NOUN
fcis-25709	229	13	cloud	cloud	NOUN
fcis-25709	229	14	reconstruction	reconstruction	NOUN
fcis-25709	229	15	using	use	VERB
fcis-25709	229	16	a	a	DET
fcis-25709	229	17	deep	deep	ADJ
fcis-25709	229	18	pyramid	pyramid	NOUN
fcis-25709	229	19	network[c]//2019	network[c]//2019	ADP
fcis-25709	229	20	ieee	ieee	NOUN
fcis-25709	229	21	winter	winter	NOUN
fcis-25709	229	22	conference	conference	NOUN
fcis-25709	229	23	on	on	ADP
fcis-25709	229	24	applications	application	NOUN
fcis-25709	229	25	of	of	ADP
fcis-25709	229	26	computer	computer	NOUN
fcis-25709	229	27	vision	vision	NOUN
fcis-25709	229	28	(	(	PUNCT
fcis-25709	229	29	wacv	wacv	NOUN
fcis-25709	229	30	)	)	PUNCT
fcis-25709	229	31	.	.	PUNCT
fcis-25709	230	1	ieee	ieee	NOUN
fcis-25709	230	2	,	,	PUNCT
fcis-25709	230	3	2019	2019	NUM
fcis-25709	230	4	:	:	SYM
fcis-25709	230	5	1052	1052	NUM
fcis-25709	230	6	-	-	SYM
fcis-25709	230	7	1060	1060	NUM
fcis-25709	230	8	.	.	PUNCT
fcis-25709	231	1	[	[	X
fcis-25709	231	2	5	5	X
fcis-25709	231	3	]	]	PUNCT
fcis-25709	231	4	diab	diab	PROPN
fcis-25709	231	5	a	a	PRON
fcis-25709	231	6	,	,	PUNCT
fcis-25709	231	7	kashef	kashef	ADJ
fcis-25709	231	8	r	r	NOUN
fcis-25709	231	9	,	,	PUNCT
fcis-25709	231	10	shaker	shaker	NOUN
fcis-25709	231	11	a.	a.	NOUN
fcis-25709	231	12	deep	deep	PROPN
fcis-25709	231	13	learning	learning	NOUN
fcis-25709	231	14	for	for	ADP
fcis-25709	231	15	lidar	lidar	NOUN
fcis-25709	231	16	point	point	NOUN
fcis-25709	231	17	cloud	cloud	NOUN
fcis-25709	231	18	classification	classification	NOUN
fcis-25709	231	19	in	in	ADP
fcis-25709	231	20	remote	remote	ADJ
fcis-25709	231	21	sensing[j	sensing[j	NOUN
fcis-25709	231	22	]	]	PUNCT
fcis-25709	231	23	.	.	PUNCT
fcis-25709	232	1	sensors	sensor	NOUN
fcis-25709	232	2	,	,	PUNCT
fcis-25709	232	3	2022	2022	NUM
fcis-25709	232	4	,	,	PUNCT
fcis-25709	232	5	22(20	22(20	NUM
fcis-25709	232	6	):	):	PUNCT
fcis-25709	232	7	7868	7868	NUM
fcis-25709	232	8	.	.	PUNCT
fcis-25709	233	1	[	[	X
fcis-25709	233	2	6	6	NUM
fcis-25709	233	3	]	]	X
fcis-25709	233	4	zhang	zhang	PROPN
fcis-25709	233	5	j	j	PROPN
fcis-25709	233	6	,	,	PUNCT
fcis-25709	233	7	zhao	zhao	PROPN
fcis-25709	233	8	x	x	PROPN
fcis-25709	233	9	,	,	PUNCT
fcis-25709	233	10	chen	chen	PROPN
fcis-25709	233	11	z	z	PROPN
fcis-25709	233	12	,	,	PUNCT
fcis-25709	233	13	et	et	PROPN
fcis-25709	233	14	al	al	PROPN
fcis-25709	233	15	.	.	PUNCT
fcis-25709	234	1	a	a	DET
fcis-25709	234	2	review	review	NOUN
fcis-25709	234	3	of	of	ADP
fcis-25709	234	4	deep	deep	ADJ
fcis-25709	234	5	learningbased	learningbase	VERB
fcis-25709	234	6	semantic	semantic	ADJ
fcis-25709	234	7	segmentation	segmentation	NOUN
fcis-25709	234	8	for	for	ADP
fcis-25709	234	9	point	point	NOUN
fcis-25709	234	10	cloud[j	cloud[j	NOUN
fcis-25709	234	11	]	]	PUNCT
fcis-25709	234	12	.	.	PUNCT
fcis-25709	235	1	ieee	ieee	NOUN
fcis-25709	235	2	access	access	NOUN
fcis-25709	235	3	,	,	PUNCT
fcis-25709	235	4	2019	2019	NUM
fcis-25709	235	5	,	,	PUNCT
fcis-25709	235	6	7	7	NUM
fcis-25709	235	7	:	:	SYM
fcis-25709	235	8	179118	179118	NUM
fcis-25709	235	9	-	-	SYM
fcis-25709	235	10	179133	179133	NUM
fcis-25709	235	11	.	.	PUNCT
fcis-25709	236	1	[	[	X
fcis-25709	236	2	7	7	NUM
fcis-25709	236	3	]	]	SYM
fcis-25709	236	4	su	su	PROPN
fcis-25709	236	5	h	h	PROPN
fcis-25709	236	6	,	,	PUNCT
fcis-25709	236	7	maji	maji	PROPN
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fcis-25709	236	9	,	,	PUNCT
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fcis-25709	236	11	e	e	NOUN
fcis-25709	236	12	,	,	PUNCT
fcis-25709	236	13	et	et	PROPN
fcis-25709	236	14	al	al	PROPN
fcis-25709	236	15	.	.	PUNCT
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fcis-25709	237	2	-	-	ADJ
fcis-25709	237	3	view	view	ADJ
fcis-25709	237	4	convolutional	convolutional	ADJ
fcis-25709	237	5	neural	neural	ADJ
fcis-25709	237	6	networks	network	NOUN
fcis-25709	237	7	for	for	ADP
fcis-25709	237	8	3d	3d	NUM
fcis-25709	237	9	shape	shape	NOUN
fcis-25709	237	10	recognition[c]//proceedings	recognition[c]//proceeding	NOUN
fcis-25709	237	11	of	of	ADP
fcis-25709	237	12	the	the	DET
fcis-25709	237	13	ieee	ieee	NOUN
fcis-25709	237	14	international	international	PROPN
fcis-25709	237	15	conference	conference	NOUN
fcis-25709	237	16	on	on	ADP
fcis-25709	237	17	computer	computer	NOUN
fcis-25709	237	18	vision	vision	NOUN
fcis-25709	237	19	,	,	PUNCT
fcis-25709	237	20	2015	2015	NUM
fcis-25709	237	21	:	:	PUNCT
fcis-25709	237	22	945	945	NUM
fcis-25709	237	23	-	-	SYM
fcis-25709	237	24	953	953	NUM
fcis-25709	237	25	.	.	PUNCT
fcis-25709	238	1	[	[	X
fcis-25709	238	2	8	8	NUM
fcis-25709	238	3	]	]	PUNCT
fcis-25709	238	4	boulch	boulch	PROPN
fcis-25709	238	5	a	a	PROPN
fcis-25709	238	6	,	,	PUNCT
fcis-25709	238	7	guerry	guerry	PROPN
fcis-25709	238	8	j	j	PROPN
fcis-25709	238	9	,	,	PUNCT
fcis-25709	238	10	le	le	X
fcis-25709	238	11	saux	saux	PROPN
fcis-25709	238	12	b	b	X
fcis-25709	238	13	,	,	PUNCT
fcis-25709	238	14	et	et	PROPN
fcis-25709	238	15	al	al	PROPN
fcis-25709	238	16	.	.	PROPN
fcis-25709	238	17	snapnet	snapnet	PROPN
fcis-25709	238	18	:	:	PUNCT
fcis-25709	238	19	3d	3d	NUM
fcis-25709	238	20	point	point	NOUN
fcis-25709	238	21	cloud	cloud	ADJ
fcis-25709	238	22	semantic	semantic	ADJ
fcis-25709	238	23	labeling	labeling	NOUN
fcis-25709	238	24	with	with	ADP
fcis-25709	238	25	2d	2d	NUM
fcis-25709	238	26	deep	deep	ADJ
fcis-25709	238	27	segmentation	segmentation	NOUN
fcis-25709	238	28	networks[j	networks[j	PROPN
fcis-25709	238	29	]	]	X
fcis-25709	238	30	.	.	PUNCT
fcis-25709	239	1	computers	computer	NOUN
fcis-25709	239	2	&	&	CCONJ
fcis-25709	239	3	graphics	graphic	NOUN
fcis-25709	239	4	,	,	PUNCT
fcis-25709	239	5	2018	2018	NUM
fcis-25709	239	6	,	,	PUNCT
fcis-25709	239	7	71	71	NUM
fcis-25709	239	8	:	:	SYM
fcis-25709	239	9	189	189	NUM
fcis-25709	239	10	-	-	SYM
fcis-25709	239	11	198	198	NUM
fcis-25709	239	12	.	.	PUNCT
fcis-25709	240	1	[	[	X
fcis-25709	240	2	9	9	NUM
fcis-25709	240	3	]	]	PUNCT
fcis-25709	240	4	riegler	riegler	NOUN
fcis-25709	240	5	g	g	PROPN
fcis-25709	240	6	,	,	PUNCT
fcis-25709	240	7	ulusoy	ulusoy	ADJ
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fcis-25709	240	9	a	a	NOUN
fcis-25709	240	10	,	,	PUNCT
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fcis-25709	240	13	octnet	octnet	PROPN
fcis-25709	240	14	:	:	PUNCT
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fcis-25709	240	17	3d	3d	NUM
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fcis-25709	240	19	at	at	ADP
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fcis-25709	240	22	]	]	PUNCT
fcis-25709	240	23	.	.	PUNCT
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fcis-25709	241	2	1611	1611	NUM
fcis-25709	241	3	.	.	PUNCT
fcis-25709	242	1	05009	05009	NUM
fcis-25709	242	2	.	.	PUNCT
fcis-25709	243	1	[	[	X
fcis-25709	243	2	10	10	NUM
fcis-25709	243	3	]	]	X
fcis-25709	243	4	qi	qi	PROPN
fcis-25709	243	5	c	c	PROPN
fcis-25709	243	6	r	r	PROPN
fcis-25709	243	7	,	,	PUNCT
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fcis-25709	243	9	h	h	PROPN
fcis-25709	243	10	,	,	PUNCT
fcis-25709	243	11	mo	mo	PROPN
fcis-25709	243	12	k	k	PROPN
fcis-25709	243	13	,	,	PUNCT
fcis-25709	243	14	et	et	PROPN
fcis-25709	243	15	al	al	PROPN
fcis-25709	243	16	.	.	PUNCT
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fcis-25709	243	18	:	:	PUNCT
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fcis-25709	243	20	learning	learning	NOUN
fcis-25709	243	21	on	on	ADP
fcis-25709	243	22	point	point	NOUN
fcis-25709	243	23	sets	set	NOUN
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fcis-25709	243	25	3d	3d	NUM
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fcis-25709	243	27	and	and	CCONJ
fcis-25709	243	28	segmentation[c]//proceedings	segmentation[c]//proceeding	NOUN
fcis-25709	243	29	of	of	ADP
fcis-25709	243	30	the	the	DET
fcis-25709	243	31	ieee	ieee	NOUN
fcis-25709	243	32	conference	conference	NOUN
fcis-25709	243	33	on	on	ADP
fcis-25709	243	34	computer	computer	NOUN
fcis-25709	243	35	vision	vision	NOUN
fcis-25709	243	36	and	and	CCONJ
fcis-25709	243	37	pattern	pattern	NOUN
fcis-25709	243	38	recognition	recognition	NOUN
fcis-25709	243	39	,	,	PUNCT
fcis-25709	243	40	2017	2017	NUM
fcis-25709	243	41	:	:	PUNCT
fcis-25709	243	42	652	652	NUM
fcis-25709	243	43	-	-	SYM
fcis-25709	243	44	660	660	NUM
fcis-25709	243	45	.	.	PUNCT
fcis-25709	244	1	[	[	X
fcis-25709	244	2	11	11	NUM
fcis-25709	244	3	]	]	PUNCT
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fcis-25709	244	18	:	:	PUNCT
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fcis-25709	244	20	hierarchical	hierarchical	ADJ
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fcis-25709	244	25	sets	set	NOUN
fcis-25709	244	26	in	in	ADP
fcis-25709	244	27	a	a	DET
fcis-25709	244	28	metric	metric	ADJ
fcis-25709	244	29	space[j	space[j	NOUN
fcis-25709	244	30	]	]	PUNCT
fcis-25709	244	31	.	.	PUNCT
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fcis-25709	245	5	processing	processing	NOUN
fcis-25709	245	6	systems	system	NOUN
fcis-25709	245	7	,	,	PUNCT
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fcis-25709	245	9	,	,	PUNCT
fcis-25709	245	10	30	30	NUM
fcis-25709	245	11	.	.	PUNCT
fcis-25709	246	1	[	[	X
fcis-25709	246	2	12	12	NUM
fcis-25709	246	3	]	]	X
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fcis-25709	247	1	q	q	PROPN
fcis-25709	247	2	,	,	PUNCT
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fcis-25709	247	5	,	,	PUNCT
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fcis-25709	247	8	,	,	PUNCT
fcis-25709	247	9	et	et	PROPN
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fcis-25709	247	11	.	.	PUNCT
fcis-25709	248	1	randla	randla	NOUN
fcis-25709	248	2	-	-	PUNCT
fcis-25709	248	3	net	net	NOUN
fcis-25709	248	4	:	:	PUNCT
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fcis-25709	248	8	of	of	ADP
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fcis-25709	248	10	-	-	PUNCT
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fcis-25709	248	13	clouds[c]//proceedings	clouds[c]//proceeding	NOUN
fcis-25709	248	14	of	of	ADP
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fcis-25709	248	16	ieee	ieee	NOUN
fcis-25709	248	17	/	/	SYM
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fcis-25709	248	19	conference	conference	NOUN
fcis-25709	248	20	on	on	ADP
fcis-25709	248	21	computer	computer	NOUN
fcis-25709	248	22	vision	vision	NOUN
fcis-25709	248	23	and	and	CCONJ
fcis-25709	248	24	pattern	pattern	NOUN
fcis-25709	248	25	recognition	recognition	NOUN
fcis-25709	248	26	,	,	PUNCT
fcis-25709	248	27	2020	2020	NUM
fcis-25709	248	28	:	:	PUNCT
fcis-25709	248	29	11108	11108	NUM
fcis-25709	248	30	-	-	SYM
fcis-25709	248	31	11117	11117	NUM
fcis-25709	248	32	.	.	PUNCT
fcis-25709	249	1	[	[	X
fcis-25709	249	2	13	13	NUM
fcis-25709	249	3	]	]	SYM
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fcis-25709	249	8	r	r	NOUN
fcis-25709	249	9	,	,	PUNCT
fcis-25709	249	10	sun	sun	NOUN
fcis-25709	249	11	m	m	PROPN
fcis-25709	249	12	,	,	PUNCT
fcis-25709	249	13	et	et	PROPN
fcis-25709	249	14	al	al	PROPN
fcis-25709	249	15	.	.	PROPN
fcis-25709	249	16	pointcnn	pointcnn	PROPN
fcis-25709	249	17	:	:	PUNCT
fcis-25709	249	18	convolution	convolution	NOUN
fcis-25709	249	19	on	on	ADP
fcis-25709	249	20	xtransformed	xtransformed	PROPN
fcis-25709	249	21	points[j	points[j	PROPN
fcis-25709	249	22	]	]	PUNCT
fcis-25709	249	23	.	.	PUNCT
fcis-25709	250	1	advances	advance	NOUN
fcis-25709	250	2	in	in	ADP
fcis-25709	250	3	neural	neural	ADJ
fcis-25709	250	4	information	information	NOUN
fcis-25709	250	5	processing	processing	NOUN
fcis-25709	250	6	systems	system	NOUN
fcis-25709	250	7	,	,	PUNCT
fcis-25709	250	8	2018	2018	NUM
fcis-25709	250	9	,	,	PUNCT
fcis-25709	250	10	31	31	NUM
fcis-25709	250	11	.	.	PUNCT
fcis-25709	251	1	[	[	X
fcis-25709	251	2	14	14	NUM
fcis-25709	251	3	]	]	X
fcis-25709	251	4	wu	wu	PROPN
fcis-25709	251	5	w	w	PROPN
fcis-25709	251	6	,	,	PUNCT
fcis-25709	251	7	qi	qi	PROPN
fcis-25709	251	8	z	z	PROPN
fcis-25709	251	9	,	,	PUNCT
fcis-25709	251	10	fuxin	fuxin	PROPN
fcis-25709	251	11	l.	l.	PROPN
fcis-25709	251	12	pointconv	pointconv	PROPN
fcis-25709	251	13	:	:	PUNCT
fcis-25709	251	14	deep	deep	ADJ
fcis-25709	251	15	convolutional	convolutional	ADJ
fcis-25709	251	16	networks	network	NOUN
fcis-25709	251	17	on	on	ADP
fcis-25709	251	18	3d	3d	NUM
fcis-25709	251	19	point	point	NOUN
fcis-25709	251	20	clouds[c]//proceedings	clouds[c]//proceeding	NOUN
fcis-25709	251	21	of	of	ADP
fcis-25709	251	22	the	the	DET
fcis-25709	251	23	ieee	ieee	NOUN
fcis-25709	251	24	/	/	SYM
fcis-25709	251	25	cvf	cvf	NOUN
fcis-25709	251	26	conference	conference	NOUN
fcis-25709	251	27	on	on	ADP
fcis-25709	251	28	computer	computer	NOUN
fcis-25709	251	29	vision	vision	NOUN
fcis-25709	251	30	and	and	CCONJ
fcis-25709	251	31	pattern	pattern	NOUN
fcis-25709	251	32	recognition	recognition	NOUN
fcis-25709	251	33	,	,	PUNCT
fcis-25709	251	34	2019	2019	NUM
fcis-25709	251	35	:	:	PUNCT
fcis-25709	251	36	9621	9621	NUM
fcis-25709	251	37	-	-	SYM
fcis-25709	251	38	9630	9630	NUM
fcis-25709	251	39	.	.	PUNCT
fcis-25709	252	1	[	[	X
fcis-25709	252	2	15	15	NUM
fcis-25709	252	3	]	]	X
fcis-25709	252	4	du	du	PROPN
fcis-25709	252	5	j	j	PROPN
fcis-25709	252	6	and	and	CCONJ
fcis-25709	252	7	cai	cai	PROPN
fcis-25709	252	8	g	g	PROPN
fcis-25709	252	9	r.	r.	PROPN
fcis-25709	252	10	2021	2021	NUM
fcis-25709	252	11	.	.	PUNCT
fcis-25709	253	1	point	point	NOUN
fcis-25709	253	2	cloud	cloud	ADJ
fcis-25709	253	3	semantic	semantic	ADJ
fcis-25709	253	4	segmentation	segmentation	NOUN
fcis-25709	253	5	method	method	NOUN
fcis-25709	253	6	based	base	VERB
fcis-25709	253	7	on	on	ADP
fcis-25709	253	8	multi	multi	ADJ
fcis-25709	253	9	-	-	ADJ
fcis-25709	253	10	feature	feature	ADJ
fcis-25709	253	11	fusion	fusion	NOUN
fcis-25709	253	12	and	and	CCONJ
fcis-25709	253	13	residual	residual	ADJ
fcis-25709	253	14	optimization	optimization	NOUN
fcis-25709	254	1	[	[	X
fcis-25709	254	2	j	j	X
fcis-25709	254	3	]	]	X
fcis-25709	254	4	.	.	PUNCT
fcis-25709	255	1	journal	journal	PROPN
fcis-25709	255	2	of	of	ADP
fcis-25709	255	3	image	image	NOUN
fcis-25709	255	4	and	and	CCONJ
fcis-25709	255	5	graphics,2021	graphics,2021	NOUN
fcis-25709	255	6	,	,	PUNCT
fcis-25709	255	7	(	(	PUNCT
fcis-25709	255	8	05	05	NUM
fcis-25709	255	9	):	):	PUNCT
fcis-25709	255	10	1105	1105	NUM
fcis-25709	255	11	-	-	SYM
fcis-25709	255	12	1116	1116	NUM
fcis-25709	255	13	.	.	PUNCT
fcis-25709	256	1	[	[	X
fcis-25709	256	2	16	16	NUM
fcis-25709	256	3	]	]	X
fcis-25709	256	4	liu	liu	PROPN
fcis-25709	256	5	z	z	PROPN
fcis-25709	256	6	,	,	PUNCT
fcis-25709	256	7	hu	hu	PROPN
fcis-25709	256	8	h	h	PROPN
fcis-25709	256	9	,	,	PUNCT
fcis-25709	256	10	cao	cao	PROPN
fcis-25709	256	11	y	y	PROPN
fcis-25709	256	12	,	,	PUNCT
fcis-25709	256	13	et	et	PROPN
fcis-25709	256	14	al	al	PROPN
fcis-25709	256	15	.	.	PUNCT
fcis-25709	257	1	a	a	DET
fcis-25709	257	2	closer	close	ADJ
fcis-25709	257	3	look	look	NOUN
fcis-25709	257	4	at	at	ADP
fcis-25709	257	5	local	local	ADJ
fcis-25709	257	6	aggregation	aggregation	NOUN
fcis-25709	257	7	operators	operator	NOUN
fcis-25709	257	8	in	in	ADP
fcis-25709	257	9	point	point	NOUN
fcis-25709	257	10	cloud	cloud	NOUN
fcis-25709	257	11	analysis[c]//computer	analysis[c]//computer	PROPN
fcis-25709	257	12	vision	vision	NOUN
fcis-25709	257	13	–	–	PUNCT
fcis-25709	257	14	eccv	eccv	ADJ
fcis-25709	257	15	2020	2020	NUM
fcis-25709	257	16	:	:	PUNCT
fcis-25709	257	17	16th	16th	ADJ
fcis-25709	257	18	european	european	ADJ
fcis-25709	257	19	conference	conference	PROPN
fcis-25709	257	20	,	,	PUNCT
fcis-25709	257	21	glasgow	glasgow	PROPN
fcis-25709	257	22	,	,	PUNCT
fcis-25709	257	23	uk	uk	PROPN
fcis-25709	257	24	,	,	PUNCT
fcis-25709	257	25	august	august	PROPN
fcis-25709	257	26	23	23	NUM
fcis-25709	257	27	–	–	PUNCT
fcis-25709	257	28	28	28	NUM
fcis-25709	257	29	,	,	PUNCT
fcis-25709	257	30	2020	2020	NUM
fcis-25709	257	31	,	,	PUNCT
fcis-25709	257	32	proceedings	proceeding	NOUN
fcis-25709	257	33	,	,	PUNCT
fcis-25709	257	34	part	part	NOUN
fcis-25709	257	35	xxiii	xxiii	PROPN
fcis-25709	257	36	16	16	NUM
fcis-25709	257	37	.	.	PUNCT
fcis-25709	258	1	springer	springer	NOUN
fcis-25709	258	2	international	international	ADJ
fcis-25709	258	3	publishing	publishing	NOUN
fcis-25709	258	4	,	,	PUNCT
fcis-25709	258	5	2020	2020	NUM
fcis-25709	258	6	:	:	PUNCT
fcis-25709	258	7	326	326	NUM
fcis-25709	258	8	-	-	SYM
fcis-25709	258	9	342	342	NUM
fcis-25709	258	10	.	.	PUNCT
fcis-25709	259	1	[	[	X
fcis-25709	259	2	17	17	NUM
fcis-25709	259	3	]	]	X
fcis-25709	259	4	xu	xu	PROPN
fcis-25709	259	5	m	m	PROPN
fcis-25709	259	6	,	,	PUNCT
fcis-25709	259	7	ding	de	VERB
fcis-25709	259	8	r	r	NOUN
fcis-25709	259	9	,	,	PUNCT
fcis-25709	259	10	zhao	zhao	PROPN
fcis-25709	259	11	h	h	NOUN
fcis-25709	259	12	,	,	PUNCT
fcis-25709	259	13	et	et	PROPN
fcis-25709	259	14	al	al	PROPN
fcis-25709	259	15	.	.	PROPN
fcis-25709	259	16	paconv	paconv	PROPN
fcis-25709	259	17	:	:	PUNCT
fcis-25709	259	18	position	position	VERB
fcis-25709	259	19	adaptive	adaptive	ADJ
fcis-25709	259	20	convolution	convolution	NOUN
fcis-25709	259	21	with	with	ADP
fcis-25709	259	22	dynamic	dynamic	ADJ
fcis-25709	259	23	kernel	kernel	NOUN
fcis-25709	259	24	assembling	assemble	VERB
fcis-25709	259	25	on	on	ADP
fcis-25709	259	26	point	point	NOUN
fcis-25709	259	27	clouds[c]//proceedings	clouds[c]//proceeding	NOUN
fcis-25709	259	28	of	of	ADP
fcis-25709	259	29	the	the	DET
fcis-25709	259	30	ieee	ieee	NOUN
fcis-25709	259	31	/	/	SYM
fcis-25709	259	32	cvf	cvf	NOUN
fcis-25709	259	33	conference	conference	NOUN
fcis-25709	259	34	on	on	ADP
fcis-25709	259	35	computer	computer	NOUN
fcis-25709	259	36	vision	vision	NOUN
fcis-25709	259	37	and	and	CCONJ
fcis-25709	259	38	pattern	pattern	NOUN
fcis-25709	259	39	recognition	recognition	NOUN
fcis-25709	259	40	,	,	PUNCT
fcis-25709	259	41	2021	2021	NUM
fcis-25709	259	42	:	:	PUNCT
fcis-25709	259	43	3173	3173	NUM
fcis-25709	259	44	-	-	SYM
fcis-25709	259	45	3182	3182	NUM
fcis-25709	259	46	.	.	PUNCT
fcis-25709	260	1	[	[	X
fcis-25709	260	2	18	18	NUM
fcis-25709	260	3	]	]	X
fcis-25709	260	4	hao	hao	PROPN
fcis-25709	260	5	w	w	PROPN
fcis-25709	260	6	,	,	PUNCT
fcis-25709	260	7	wang	wang	PROPN
fcis-25709	260	8	h	h	PROPN
fcis-25709	260	9	x	x	PROPN
fcis-25709	260	10	,	,	PUNCT
fcis-25709	260	11	wang	wang	PROPN
fcis-25709	260	12	y.	y.	PROPN
fcis-25709	260	13	semantic	semantic	PROPN
fcis-25709	260	14	segmentation	segmentation	NOUN
fcis-25709	260	15	of	of	ADP
fcis-25709	260	16	three	three	NUM
fcis-25709	260	17	-	-	PUNCT
fcis-25709	260	18	dimensional	dimensional	ADJ
fcis-25709	260	19	point	point	NOUN
fcis-25709	260	20	cloud	cloud	NOUN
fcis-25709	260	21	based	base	VERB
fcis-25709	260	22	on	on	ADP
fcis-25709	260	23	spatial	spatial	ADJ
fcis-25709	260	24	attention	attention	NOUN
fcis-25709	260	25	and	and	CCONJ
fcis-25709	260	26	shape	shape	NOUN
fcis-25709	260	27	feature	feature	NOUN
fcis-25709	260	28	[	[	X
fcis-25709	260	29	j	j	X
fcis-25709	260	30	]	]	X
fcis-25709	260	31	.	.	PUNCT
fcis-25709	261	1	laser	laser	NOUN
fcis-25709	261	2	and	and	CCONJ
fcis-25709	261	3	optoelectronics	optoelectronic	NOUN
fcis-25709	261	4	progress	progress	NOUN
fcis-25709	261	5	,	,	PUNCT
fcis-25709	261	6	2022	2022	NUM
fcis-25709	261	7	,	,	PUNCT
fcis-25709	261	8	59	59	NUM
fcis-25709	261	9	(	(	PUNCT
fcis-25709	261	10	8)	8)	NUM
fcis-25709	261	11	:	:	PUNCT
fcis-25709	261	12	no	no	NOUN
fcis-25709	261	13	.	.	NOUN
fcis-25709	261	14	0828004	0828004	NUM
fcis-25709	261	15	.	.	PUNCT
fcis-25709	262	1	[	[	X
fcis-25709	262	2	19	19	NUM
fcis-25709	262	3	]	]	X
fcis-25709	262	4	lin	lin	PROPN
fcis-25709	262	5	y	y	PROPN
fcis-25709	262	6	,	,	PUNCT
fcis-25709	262	7	chen	chen	PROPN
fcis-25709	262	8	l	l	PROPN
fcis-25709	262	9	,	,	PUNCT
fcis-25709	262	10	huang	huang	PROPN
fcis-25709	262	11	h	h	PROPN
fcis-25709	262	12	,	,	PUNCT
fcis-25709	262	13	et	et	PROPN
fcis-25709	262	14	al	al	PROPN
fcis-25709	262	15	.	.	PROPN
fcis-25709	263	1	beyond	beyond	ADP
fcis-25709	263	2	farthest	farth	ADJ
fcis-25709	263	3	point	point	NOUN
fcis-25709	263	4	sampling	sample	VERB
fcis-25709	263	5	in	in	ADP
fcis-25709	263	6	point	point	NOUN
fcis-25709	263	7	-	-	PUNCT
fcis-25709	263	8	wise	wise	ADJ
fcis-25709	263	9	analysis[j	analysis[j	PROPN
fcis-25709	263	10	]	]	PUNCT
fcis-25709	263	11	.	.	PUNCT
fcis-25709	264	1	arxiv	arxiv	PROPN
fcis-25709	264	2	preprint	preprint	VERB
fcis-25709	264	3	arxiv:2107.04291	arxiv:2107.04291	PROPN
fcis-25709	264	4	,	,	PUNCT
fcis-25709	264	5	2021	2021	NUM
fcis-25709	264	6	.	.	PUNCT
fcis-25709	265	1	[	[	X
fcis-25709	265	2	20	20	NUM
fcis-25709	265	3	]	]	PUNCT
fcis-25709	265	4	groh	groh	NOUN
fcis-25709	265	5	f	f	X
fcis-25709	265	6	,	,	PUNCT
fcis-25709	265	7	wieschollek	wieschollek	NOUN
fcis-25709	265	8	p	p	NOUN
fcis-25709	265	9	,	,	PUNCT
fcis-25709	265	10	lensch	lensch	ADP
fcis-25709	265	11	h	h	NOUN
fcis-25709	265	12	p	p	NOUN
fcis-25709	265	13	a.	a.	NOUN
fcis-25709	265	14	flex	flex	ADJ
fcis-25709	265	15	-	-	PUNCT
fcis-25709	265	16	convolution	convolution	NOUN
fcis-25709	265	17	:	:	PUNCT
fcis-25709	265	18	million	million	NUM
fcis-25709	265	19	-	-	PUNCT
fcis-25709	265	20	scale	scale	NOUN
fcis-25709	265	21	point	point	NOUN
fcis-25709	265	22	-	-	PUNCT
fcis-25709	265	23	cloud	cloud	NOUN
fcis-25709	265	24	learning	learning	NOUN
fcis-25709	265	25	beyond	beyond	ADP
fcis-25709	265	26	grid	grid	NOUN
fcis-25709	265	27	-	-	PUNCT
fcis-25709	265	28	worlds[c]//	worlds[c]//	VERB
fcis-25709	265	29	asian	asian	ADJ
fcis-25709	265	30	conference	conference	NOUN
fcis-25709	265	31	on	on	ADP
fcis-25709	265	32	computer	computer	NOUN
fcis-25709	265	33	vision	vision	NOUN
fcis-25709	265	34	.	.	PUNCT
fcis-25709	266	1	cham	cham	PROPN
fcis-25709	266	2	:	:	PUNCT
fcis-25709	266	3	springer	springer	NOUN
fcis-25709	266	4	international	international	ADJ
fcis-25709	266	5	publishing	publishing	NOUN
fcis-25709	266	6	,	,	PUNCT
fcis-25709	266	7	2018	2018	NUM
fcis-25709	266	8	:	:	PUNCT
fcis-25709	266	9	105	105	NUM
fcis-25709	266	10	-	-	SYM
fcis-25709	266	11	122	122	NUM
fcis-25709	266	12	.	.	PUNCT
fcis-25709	267	1	[	[	X
fcis-25709	267	2	21	21	NUM
fcis-25709	267	3	]	]	X
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fcis-25709	267	7	almeida	almeida	PROPN
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fcis-25709	267	9	,	,	PUNCT
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fcis-25709	267	11	k.	k.	PROPN
fcis-25709	267	12	resnet	resnet	PROPN
fcis-25709	267	13	in	in	ADP
fcis-25709	267	14	resnet	resnet	NOUN
fcis-25709	267	15	:	:	PUNCT
fcis-25709	267	16	generalizing	generalize	VERB
fcis-25709	267	17	residual	residual	ADJ
fcis-25709	267	18	architectures[j	architectures[j	NOUN
fcis-25709	267	19	]	]	PUNCT
fcis-25709	267	20	.	.	PUNCT
fcis-25709	268	1	arxiv	arxiv	PROPN
fcis-25709	268	2	preprint	preprint	PROPN
fcis-25709	268	3	arxiv:1603.08029	arxiv:1603.08029	PROPN
fcis-25709	268	4	,	,	PUNCT
fcis-25709	268	5	2016	2016	NUM
fcis-25709	268	6	.	.	PUNCT
fcis-25709	269	1	[	[	X
fcis-25709	269	2	22	22	NUM
fcis-25709	269	3	]	]	X
fcis-25709	269	4	lee	lee	PROPN
fcis-25709	269	5	c	c	PROPN
fcis-25709	269	6	y	y	PROPN
fcis-25709	269	7	,	,	PUNCT
fcis-25709	269	8	xie	xie	PROPN
fcis-25709	269	9	s	s	PROPN
fcis-25709	269	10	,	,	PUNCT
fcis-25709	269	11	gallagher	gallagher	PROPN
fcis-25709	269	12	p	p	PROPN
fcis-25709	269	13	,	,	PUNCT
fcis-25709	269	14	et	et	PROPN
fcis-25709	269	15	al	al	PROPN
fcis-25709	269	16	.	.	PUNCT
fcis-25709	269	17	deeply	deeply	ADV
fcis-25709	269	18	-	-	PUNCT
fcis-25709	269	19	supervised	supervise	VERB
fcis-25709	269	20	nets	net	NOUN
fcis-25709	269	21	[	[	PUNCT
fcis-25709	269	22	c]//	c]//	ADJ
fcis-25709	269	23	artificial	artificial	ADJ
fcis-25709	269	24	intelligence	intelligence	NOUN
fcis-25709	269	25	and	and	CCONJ
fcis-25709	269	26	statistics	statistic	NOUN
fcis-25709	269	27	.	.	PUNCT
fcis-25709	270	1	pmlr	pmlr	NOUN
fcis-25709	270	2	,	,	PUNCT
fcis-25709	270	3	2015	2015	NUM
fcis-25709	270	4	:	:	PUNCT
fcis-25709	270	5	562	562	NUM
fcis-25709	270	6	-	-	SYM
fcis-25709	270	7	570	570	NUM
fcis-25709	270	8	.	.	PUNCT
fcis-25709	271	1	[	[	X
fcis-25709	271	2	23	23	NUM
fcis-25709	271	3	]	]	X
fcis-25709	271	4	ke	ke	PROPN
fcis-25709	271	5	l	l	PROPN
fcis-25709	271	6	,	,	PUNCT
fcis-25709	271	7	chang	chang	PROPN
fcis-25709	271	8	m	m	PROPN
fcis-25709	271	9	c	c	PROPN
fcis-25709	271	10	,	,	PUNCT
fcis-25709	271	11	qi	qi	PROPN
fcis-25709	271	12	h	h	NOUN
fcis-25709	271	13	,	,	PUNCT
fcis-25709	271	14	et	et	PROPN
fcis-25709	271	15	al	al	PROPN
fcis-25709	271	16	.	.	PUNCT
fcis-25709	271	17	multi	multi	ADJ
fcis-25709	271	18	-	-	ADJ
fcis-25709	271	19	scale	scale	ADJ
fcis-25709	271	20	structure	structure	NOUN
fcis-25709	271	21	-	-	PUNCT
fcis-25709	271	22	aware	aware	ADJ
fcis-25709	271	23	network	network	NOUN
fcis-25709	271	24	for	for	ADP
fcis-25709	271	25	human	human	ADJ
fcis-25709	271	26	pose	pose	NOUN
fcis-25709	271	27	estimation[c]//proceedings	estimation[c]//proceeding	NOUN
fcis-25709	271	28	of	of	ADP
fcis-25709	271	29	the	the	DET
fcis-25709	271	30	european	european	ADJ
fcis-25709	271	31	conference	conference	PROPN
fcis-25709	271	32	on	on	ADP
fcis-25709	271	33	computer	computer	NOUN
fcis-25709	271	34	vision	vision	NOUN
fcis-25709	271	35	(	(	PUNCT
fcis-25709	271	36	eccv	eccv	ADV
fcis-25709	271	37	)	)	PUNCT
fcis-25709	271	38	,	,	PUNCT
fcis-25709	271	39	2018	2018	NUM
fcis-25709	271	40	:	:	PUNCT
fcis-25709	271	41	713728	713728	NUM
fcis-25709	271	42	.	.	PUNCT
fcis-25709	272	1	19	19	NUM
fcis-25709	273	1	[	[	SYM
fcis-25709	273	2	24	24	NUM
fcis-25709	273	3	]	]	PUNCT
fcis-25709	273	4	armeni	armeni	PROPN
fcis-25709	273	5	i	i	PROPN
fcis-25709	273	6	,	,	PUNCT
fcis-25709	273	7	sener	sener	NOUN
fcis-25709	273	8	o	o	PROPN
fcis-25709	273	9	,	,	PUNCT
fcis-25709	273	10	zamir	zamir	VERB
fcis-25709	273	11	a	a	DET
fcis-25709	273	12	r	r	NOUN
fcis-25709	273	13	,	,	PUNCT
fcis-25709	273	14	et	et	PROPN
fcis-25709	273	15	al	al	PROPN
fcis-25709	273	16	.	.	PROPN
fcis-25709	273	17	3d	3d	PROPN
fcis-25709	273	18	semantic	semantic	ADJ
fcis-25709	273	19	parsing	parsing	NOUN
fcis-25709	273	20	of	of	ADP
fcis-25709	273	21	large	large	ADJ
fcis-25709	273	22	-	-	PUNCT
fcis-25709	273	23	scale	scale	NOUN
fcis-25709	273	24	indoor	indoor	ADJ
fcis-25709	273	25	spaces[c]//proceedings	spaces[c]//proceeding	NOUN
fcis-25709	273	26	of	of	ADP
fcis-25709	273	27	the	the	DET
fcis-25709	273	28	ieee	ieee	NOUN
fcis-25709	273	29	conference	conference	NOUN
fcis-25709	273	30	on	on	ADP
fcis-25709	273	31	computer	computer	NOUN
fcis-25709	273	32	vision	vision	NOUN
fcis-25709	273	33	and	and	CCONJ
fcis-25709	273	34	pattern	pattern	NOUN
fcis-25709	273	35	recognition	recognition	NOUN
fcis-25709	273	36	,	,	PUNCT
fcis-25709	273	37	2016	2016	NUM
fcis-25709	273	38	:	:	PUNCT
fcis-25709	273	39	1534	1534	NUM
fcis-25709	273	40	-	-	SYM
fcis-25709	273	41	1543	1543	NUM
fcis-25709	273	42	.	.	PUNCT
fcis-25709	274	1	[	[	X
fcis-25709	274	2	25	25	NUM
fcis-25709	274	3	]	]	X
fcis-25709	274	4	babacan	babacan	PROPN
fcis-25709	274	5	k	k	PROPN
fcis-25709	274	6	,	,	PUNCT
fcis-25709	274	7	chen	chen	PROPN
fcis-25709	274	8	l	l	PROPN
fcis-25709	274	9	,	,	PUNCT
fcis-25709	274	10	sohn	sohn	PROPN
fcis-25709	274	11	g.	g.	PROPN
fcis-25709	274	12	semantic	semantic	PROPN
fcis-25709	274	13	segmentation	segmentation	NOUN
fcis-25709	274	14	of	of	ADP
fcis-25709	274	15	indoor	indoor	ADJ
fcis-25709	274	16	point	point	NOUN
fcis-25709	274	17	clouds	cloud	NOUN
fcis-25709	274	18	using	use	VERB
fcis-25709	274	19	convolutional	convolutional	ADJ
fcis-25709	274	20	neural	neural	ADJ
fcis-25709	274	21	network[j	network[j	NOUN
fcis-25709	274	22	]	]	PUNCT
fcis-25709	274	23	.	.	PUNCT
fcis-25709	275	1	isprs	isprs	NOUN
fcis-25709	275	2	annals	annal	NOUN
fcis-25709	275	3	of	of	ADP
fcis-25709	275	4	the	the	DET
fcis-25709	275	5	photogrammetry	photogrammetry	NOUN
fcis-25709	275	6	,	,	PUNCT
fcis-25709	275	7	remote	remote	ADJ
fcis-25709	275	8	sensing	sensing	NOUN
fcis-25709	275	9	and	and	CCONJ
fcis-25709	275	10	spatial	spatial	ADJ
fcis-25709	275	11	information	information	NOUN
fcis-25709	275	12	sciences	science	NOUN
fcis-25709	275	13	,	,	PUNCT
fcis-25709	275	14	2017	2017	NUM
fcis-25709	275	15	,	,	PUNCT
fcis-25709	275	16	4	4	NUM
fcis-25709	275	17	:	:	SYM
fcis-25709	275	18	101	101	NUM
fcis-25709	275	19	-	-	SYM
fcis-25709	275	20	108	108	NUM
fcis-25709	275	21	.	.	PUNCT
fcis-25709	276	1	[	[	X
fcis-25709	276	2	26	26	NUM
fcis-25709	276	3	]	]	PUNCT
fcis-25709	276	4	rottensteiner	rottensteiner	NOUN
fcis-25709	276	5	f	f	PROPN
fcis-25709	276	6	,	,	PUNCT
fcis-25709	276	7	sohn	sohn	PROPN
fcis-25709	276	8	g	g	PROPN
fcis-25709	276	9	,	,	PUNCT
fcis-25709	276	10	gerke	gerke	NOUN
fcis-25709	276	11	m	m	PROPN
fcis-25709	276	12	,	,	PUNCT
fcis-25709	276	13	et	et	PROPN
fcis-25709	276	14	al	al	PROPN
fcis-25709	276	15	.	.	PROPN
fcis-25709	276	16	results	result	NOUN
fcis-25709	276	17	of	of	ADP
fcis-25709	276	18	the	the	DET
fcis-25709	276	19	isprs	isprs	NOUN
fcis-25709	276	20	benchmark	benchmark	NOUN
fcis-25709	276	21	on	on	ADP
fcis-25709	276	22	urban	urban	ADJ
fcis-25709	276	23	object	object	NOUN
fcis-25709	276	24	detection	detection	NOUN
fcis-25709	276	25	and	and	CCONJ
fcis-25709	276	26	3d	3d	NUM
fcis-25709	276	27	building	building	NOUN
fcis-25709	276	28	reconstruction	reconstruction	NOUN
fcis-25709	277	1	[	[	X
fcis-25709	277	2	j	j	X
fcis-25709	277	3	]	]	X
fcis-25709	277	4	.	.	PUNCT
fcis-25709	278	1	isprs	isprs	PROPN
fcis-25709	278	2	journal	journal	PROPN
fcis-25709	278	3	of	of	ADP
fcis-25709	278	4	photogrammetry	photogrammetry	NOUN
fcis-25709	278	5	and	and	CCONJ
fcis-25709	278	6	remote	remote	ADJ
fcis-25709	278	7	sensing	sensing	NOUN
fcis-25709	278	8	,	,	PUNCT
fcis-25709	278	9	2014	2014	NUM
fcis-25709	278	10	,	,	PUNCT
fcis-25709	278	11	93	93	NUM
fcis-25709	278	12	:	:	SYM
fcis-25709	278	13	256	256	NUM
fcis-25709	278	14	-	-	SYM
fcis-25709	278	15	271	271	NUM
fcis-25709	278	16	.	.	PUNCT
fcis-25709	279	1	[	[	X
fcis-25709	279	2	27	27	NUM
fcis-25709	279	3	]	]	X
fcis-25709	279	4	phan	phan	NOUN
fcis-25709	279	5	a	a	DET
fcis-25709	279	6	v	v	NOUN
fcis-25709	279	7	,	,	PUNCT
fcis-25709	279	8	le	le	X
fcis-25709	279	9	nguyen	nguyen	PROPN
fcis-25709	279	10	m	m	PROPN
fcis-25709	279	11	,	,	PUNCT
fcis-25709	279	12	nguyen	nguyen	PROPN
fcis-25709	279	13	y	y	PROPN
fcis-25709	279	14	l	l	PROPN
fcis-25709	279	15	h	h	NOUN
fcis-25709	279	16	,	,	PUNCT
fcis-25709	279	17	et	et	PROPN
fcis-25709	279	18	al	al	PROPN
fcis-25709	279	19	.	.	PROPN
fcis-25709	279	20	dgcnn	dgcnn	PROPN
fcis-25709	279	21	:	:	PUNCT
fcis-25709	279	22	a	a	DET
fcis-25709	279	23	convolutional	convolutional	ADJ
fcis-25709	279	24	neural	neural	ADJ
fcis-25709	279	25	network	network	NOUN
fcis-25709	279	26	over	over	ADP
fcis-25709	279	27	large	large	ADJ
fcis-25709	279	28	-	-	PUNCT
fcis-25709	279	29	scale	scale	NOUN
fcis-25709	279	30	labeled	label	VERB
fcis-25709	279	31	graphs	graph	NOUN
fcis-25709	279	32	[	[	X
fcis-25709	279	33	j	j	X
fcis-25709	279	34	]	]	X
fcis-25709	279	35	.	.	PUNCT
fcis-25709	280	1	neural	neural	ADJ
fcis-25709	280	2	networks	network	NOUN
fcis-25709	280	3	,	,	PUNCT
fcis-25709	280	4	2018	2018	NUM
fcis-25709	280	5	,	,	PUNCT
fcis-25709	280	6	108	108	NUM
fcis-25709	280	7	:	:	SYM
fcis-25709	280	8	533	533	NUM
fcis-25709	280	9	-	-	SYM
fcis-25709	280	10	543	543	NUM
fcis-25709	280	11	.	.	PUNCT
fcis-25709	281	1	[	[	X
fcis-25709	281	2	28	28	NUM
fcis-25709	281	3	]	]	X
fcis-25709	281	4	deng	deng	PROPN
fcis-25709	281	5	s	s	PROPN
fcis-25709	281	6	,	,	PUNCT
fcis-25709	281	7	dong	dong	PROPN
fcis-25709	281	8	q.	q.	PROPN
fcis-25709	281	9	ga	ga	PROPN
fcis-25709	281	10	-	-	PUNCT
fcis-25709	281	11	net	net	NOUN
fcis-25709	281	12	:	:	PUNCT
fcis-25709	281	13	global	global	ADJ
fcis-25709	281	14	attention	attention	NOUN
fcis-25709	281	15	network	network	NOUN
fcis-25709	281	16	for	for	ADP
fcis-25709	281	17	point	point	NOUN
fcis-25709	281	18	cloud	cloud	NOUN
fcis-25709	281	19	semantic	semantic	ADJ
fcis-25709	281	20	segmentation[j	segmentation[j	PROPN
fcis-25709	281	21	]	]	PUNCT
fcis-25709	281	22	.	.	PUNCT
fcis-25709	282	1	ieee	ieee	PROPN
fcis-25709	282	2	signal	signal	NOUN
fcis-25709	282	3	processing	processing	NOUN
fcis-25709	282	4	letters	letter	NOUN
fcis-25709	282	5	,	,	PUNCT
fcis-25709	282	6	2021	2021	NUM
fcis-25709	282	7	,	,	PUNCT
fcis-25709	282	8	28	28	NUM
fcis-25709	282	9	:	:	SYM
fcis-25709	282	10	1300	1300	NUM
fcis-25709	282	11	-	-	SYM
fcis-25709	282	12	1304	1304	NUM
fcis-25709	282	13	.	.	PUNCT
fcis-25709	283	1	[	[	X
fcis-25709	283	2	29	29	NUM
fcis-25709	283	3	]	]	X
fcis-25709	283	4	zhao	zhao	PROPN
fcis-25709	283	5	h	h	PROPN
fcis-25709	283	6	,	,	PUNCT
fcis-25709	283	7	jiang	jiang	PROPN
fcis-25709	283	8	l	l	PROPN
fcis-25709	283	9	,	,	PUNCT
fcis-25709	283	10	fu	fu	PROPN
fcis-25709	283	11	c	c	PROPN
fcis-25709	283	12	w	w	PROPN
fcis-25709	283	13	,	,	PUNCT
fcis-25709	283	14	et	et	PROPN
fcis-25709	283	15	al	al	PROPN
fcis-25709	283	16	.	.	PUNCT
fcis-25709	284	1	pointweb	pointweb	PROPN
fcis-25709	284	2	:	:	PUNCT
fcis-25709	284	3	enhancing	enhance	VERB
fcis-25709	284	4	local	local	ADJ
fcis-25709	284	5	neighborhood	neighborhood	NOUN
fcis-25709	284	6	features	feature	NOUN
fcis-25709	284	7	for	for	ADP
fcis-25709	284	8	point	point	NOUN
fcis-25709	284	9	cloud	cloud	ADJ
fcis-25709	284	10	processing[c]//	processing[c]//	ADJ
fcis-25709	284	11	proceedings	proceeding	NOUN
fcis-25709	284	12	of	of	ADP
fcis-25709	284	13	the	the	DET
fcis-25709	284	14	ieee	ieee	NOUN
fcis-25709	284	15	/	/	SYM
fcis-25709	284	16	cvf	cvf	NOUN
fcis-25709	284	17	conference	conference	NOUN
fcis-25709	284	18	on	on	ADP
fcis-25709	284	19	computer	computer	NOUN
fcis-25709	284	20	vision	vision	NOUN
fcis-25709	284	21	and	and	CCONJ
fcis-25709	284	22	pattern	pattern	NOUN
fcis-25709	284	23	recognition	recognition	NOUN
fcis-25709	284	24	,	,	PUNCT
fcis-25709	284	25	2019	2019	NUM
fcis-25709	284	26	:	:	PUNCT
fcis-25709	284	27	5565	5565	NUM
fcis-25709	284	28	-	-	SYM
fcis-25709	284	29	5573	5573	NUM
fcis-25709	284	30	.	.	PUNCT
fcis-25709	285	1	[	[	X
fcis-25709	285	2	30	30	NUM
fcis-25709	285	3	]	]	X
fcis-25709	285	4	shuai	shuai	PROPN
fcis-25709	285	5	h	h	PROPN
fcis-25709	285	6	,	,	PUNCT
fcis-25709	285	7	xu	xu	PROPN
fcis-25709	286	1	x	x	PROPN
fcis-25709	286	2	,	,	PUNCT
fcis-25709	286	3	liu	liu	PROPN
fcis-25709	286	4	q.	q.	PROPN
fcis-25709	286	5	backward	backward	PROPN
fcis-25709	286	6	attentive	attentive	ADJ
fcis-25709	286	7	fusing	fuse	VERB
fcis-25709	286	8	network	network	NOUN
fcis-25709	286	9	with	with	ADP
fcis-25709	286	10	local	local	ADJ
fcis-25709	286	11	aggregation	aggregation	NOUN
fcis-25709	286	12	classifier	classifier	NOUN
fcis-25709	286	13	for	for	ADP
fcis-25709	286	14	3d	3d	NUM
fcis-25709	286	15	point	point	NOUN
fcis-25709	286	16	cloud	cloud	ADJ
fcis-25709	286	17	semantic	semantic	ADJ
fcis-25709	286	18	segmentation	segmentation	NOUN
fcis-25709	287	1	[	[	X
fcis-25709	287	2	j	j	X
fcis-25709	287	3	]	]	X
fcis-25709	287	4	.	.	PUNCT
fcis-25709	288	1	ieee	ieee	NOUN
fcis-25709	288	2	transactions	transaction	NOUN
fcis-25709	288	3	on	on	ADP
fcis-25709	288	4	image	image	NOUN
fcis-25709	288	5	processing	processing	NOUN
fcis-25709	288	6	,	,	PUNCT
fcis-25709	288	7	2021	2021	NUM
fcis-25709	288	8	,	,	PUNCT
fcis-25709	288	9	30	30	NUM
fcis-25709	288	10	:	:	SYM
fcis-25709	288	11	4973	4973	NUM
fcis-25709	288	12	-	-	SYM
fcis-25709	288	13	4984	4984	NUM
fcis-25709	288	14	.	.	PUNCT
fcis-25709	289	1	[	[	X
fcis-25709	289	2	31	31	NUM
fcis-25709	289	3	]	]	X
fcis-25709	289	4	fan	fan	PROPN
fcis-25709	289	5	s	s	PROPN
fcis-25709	289	6	,	,	PUNCT
fcis-25709	289	7	dong	dong	PROPN
fcis-25709	289	8	q	q	PROPN
fcis-25709	289	9	,	,	PUNCT
fcis-25709	289	10	zhu	zhu	PROPN
fcis-25709	289	11	f	f	X
fcis-25709	289	12	,	,	PUNCT
fcis-25709	289	13	et	et	PROPN
fcis-25709	289	14	al	al	PROPN
fcis-25709	289	15	.	.	PUNCT
fcis-25709	289	16	scf	scf	PROPN
fcis-25709	289	17	-	-	PUNCT
fcis-25709	289	18	net	net	NOUN
fcis-25709	289	19	:	:	PUNCT
fcis-25709	289	20	learning	learn	VERB
fcis-25709	289	21	spatial	spatial	ADJ
fcis-25709	289	22	contextual	contextual	ADJ
fcis-25709	289	23	features	feature	NOUN
fcis-25709	289	24	for	for	ADP
fcis-25709	289	25	large	large	ADJ
fcis-25709	289	26	-	-	PUNCT
fcis-25709	289	27	scale	scale	NOUN
fcis-25709	289	28	point	point	NOUN
fcis-25709	289	29	cloud	cloud	NOUN
fcis-25709	289	30	segmentation	segmentation	NOUN
fcis-25709	289	31	[	[	X
fcis-25709	289	32	c]//	c]//	ADJ
fcis-25709	289	33	proceedings	proceeding	NOUN
fcis-25709	289	34	of	of	ADP
fcis-25709	289	35	the	the	DET
fcis-25709	289	36	ieee	ieee	NOUN
fcis-25709	289	37	/	/	SYM
fcis-25709	289	38	cvf	cvf	NOUN
fcis-25709	289	39	conference	conference	NOUN
fcis-25709	289	40	on	on	ADP
fcis-25709	289	41	computer	computer	NOUN
fcis-25709	289	42	vision	vision	NOUN
fcis-25709	289	43	and	and	CCONJ
fcis-25709	289	44	pattern	pattern	NOUN
fcis-25709	289	45	recognition	recognition	NOUN
fcis-25709	289	46	,	,	PUNCT
fcis-25709	289	47	2021	2021	NUM
fcis-25709	289	48	:	:	PUNCT
fcis-25709	289	49	14504	14504	NUM
fcis-25709	289	50	-	-	SYM
fcis-25709	289	51	14513	14513	NUM
fcis-25709	289	52	.	.	PUNCT