id	sid	tid	token	lemma	pos
fcis-2707	1	1	frontiers	frontier	NOUN
fcis-2707	1	2	in	in	ADP
fcis-2707	1	3	computing	computing	NOUN
fcis-2707	1	4	and	and	CCONJ
fcis-2707	1	5	intelligent	intelligent	ADJ
fcis-2707	1	6	systems	system	NOUN
fcis-2707	1	7	issn	issn	VERB
fcis-2707	1	8	:	:	PUNCT
fcis-2707	1	9	2832	2832	NUM
fcis-2707	1	10	-	-	SYM
fcis-2707	1	11	6024	6024	NUM
fcis-2707	1	12	|	|	NOUN
fcis-2707	1	13	vol	vol	NOUN
fcis-2707	1	14	.	.	PROPN
fcis-2707	2	1	2	2	NUM
fcis-2707	2	2	,	,	PUNCT
fcis-2707	2	3	no	no	INTJ
fcis-2707	2	4	.	.	NOUN
fcis-2707	2	5	1	1	NUM
fcis-2707	2	6	,	,	PUNCT
fcis-2707	2	7	2022	2022	NUM
fcis-2707	2	8	35	35	NUM
fcis-2707	2	9	hybrid	hybrid	ADJ
fcis-2707	2	10	attention	attention	NOUN
fcis-2707	2	11	fusion	fusion	NOUN
fcis-2707	2	12	in	in	ADP
fcis-2707	2	13	dense	dense	ADJ
fcis-2707	2	14	crowd	crowd	NOUN
fcis-2707	2	15	counting	count	VERB
fcis-2707	2	16	suyu	suyu	ADJ
fcis-2707	2	17	han	han	PROPN
fcis-2707	2	18	*	*	PROPN
fcis-2707	2	19	college	college	PROPN
fcis-2707	2	20	of	of	ADP
fcis-2707	2	21	computer	computer	NOUN
fcis-2707	2	22	science	science	PROPN
fcis-2707	2	23	&	&	CCONJ
fcis-2707	2	24	technology	technology	PROPN
fcis-2707	2	25	,	,	PUNCT
fcis-2707	2	26	qingdao	qingdao	PROPN
fcis-2707	2	27	university	university	PROPN
fcis-2707	2	28	,	,	PUNCT
fcis-2707	2	29	qingdao	qingdao	PROPN
fcis-2707	2	30	266071	266071	NUM
fcis-2707	2	31	,	,	PUNCT
fcis-2707	2	32	shandong	shandong	PROPN
fcis-2707	2	33	,	,	PUNCT
fcis-2707	2	34	china	china	PROPN
fcis-2707	2	35	*	*	PUNCT
fcis-2707	2	36	corresponding	correspond	VERB
fcis-2707	2	37	author	author	NOUN
fcis-2707	2	38	:	:	PUNCT
fcis-2707	2	39	email	email	NOUN
fcis-2707	2	40	:	:	PUNCT
fcis-2707	3	1	mail.hsy@qq.com	mail.hsy@qq.com	X
fcis-2707	3	2	.	.	PUNCT
fcis-2707	4	1	abstract	abstract	ADJ
fcis-2707	4	2	:	:	PUNCT
fcis-2707	4	3	one	one	NUM
fcis-2707	4	4	of	of	ADP
fcis-2707	4	5	appealing	appealing	ADJ
fcis-2707	4	6	approaches	approach	NOUN
fcis-2707	4	7	to	to	ADP
fcis-2707	4	8	guiding	guide	VERB
fcis-2707	4	9	deep	deep	ADJ
fcis-2707	4	10	parameter	parameter	NOUN
fcis-2707	4	11	optimization	optimization	NOUN
fcis-2707	4	12	,	,	PUNCT
fcis-2707	4	13	is	be	AUX
fcis-2707	4	14	attentional	attentional	ADJ
fcis-2707	4	15	supervision	supervision	NOUN
fcis-2707	4	16	,	,	PUNCT
fcis-2707	4	17	which	which	PRON
fcis-2707	4	18	inspires	inspire	VERB
fcis-2707	4	19	intelligence	intelligence	NOUN
fcis-2707	4	20	in	in	ADP
fcis-2707	4	21	complex	complex	ADJ
fcis-2707	4	22	networks	network	NOUN
fcis-2707	4	23	at	at	ADP
fcis-2707	4	24	a	a	DET
fcis-2707	4	25	fraction	fraction	NOUN
fcis-2707	4	26	of	of	ADP
fcis-2707	4	27	the	the	DET
fcis-2707	4	28	cost	cost	NOUN
fcis-2707	4	29	,	,	PUNCT
fcis-2707	4	30	but	but	CCONJ
fcis-2707	4	31	there	there	PRON
fcis-2707	4	32	is	be	VERB
fcis-2707	4	33	still	still	ADV
fcis-2707	4	34	room	room	NOUN
fcis-2707	4	35	for	for	ADP
fcis-2707	4	36	improvement	improvement	NOUN
fcis-2707	4	37	.	.	PUNCT
fcis-2707	5	1	first	first	ADV
fcis-2707	5	2	,	,	PUNCT
fcis-2707	5	3	the	the	DET
fcis-2707	5	4	real	real	ADV
fcis-2707	5	5	dense	dense	ADJ
fcis-2707	5	6	scene	scene	NOUN
fcis-2707	5	7	with	with	ADP
fcis-2707	5	8	varying	vary	VERB
fcis-2707	5	9	scales	scale	NOUN
fcis-2707	5	10	and	and	CCONJ
fcis-2707	5	11	uneven	uneven	ADJ
fcis-2707	5	12	density	density	NOUN
fcis-2707	5	13	distribution	distribution	NOUN
fcis-2707	5	14	of	of	ADP
fcis-2707	5	15	human	human	ADJ
fcis-2707	5	16	heads	head	NOUN
fcis-2707	5	17	,	,	PUNCT
fcis-2707	5	18	the	the	DET
fcis-2707	5	19	density	density	NOUN
fcis-2707	5	20	map	map	NOUN
fcis-2707	5	21	can	can	AUX
fcis-2707	5	22	not	not	PART
fcis-2707	5	23	be	be	AUX
fcis-2707	5	24	clearly	clearly	ADV
fcis-2707	5	25	expressed	express	VERB
fcis-2707	5	26	.	.	PUNCT
fcis-2707	6	1	second	second	ADV
fcis-2707	6	2	,	,	PUNCT
fcis-2707	6	3	the	the	DET
fcis-2707	6	4	heavily	heavily	ADV
fcis-2707	6	5	occluded	occluded	ADJ
fcis-2707	6	6	areas	area	NOUN
fcis-2707	6	7	are	be	AUX
fcis-2707	6	8	extremely	extremely	ADV
fcis-2707	6	9	similar	similar	ADJ
fcis-2707	6	10	to	to	ADP
fcis-2707	6	11	the	the	DET
fcis-2707	6	12	complex	complex	ADJ
fcis-2707	6	13	background	background	NOUN
fcis-2707	6	14	,	,	PUNCT
fcis-2707	6	15	which	which	PRON
fcis-2707	6	16	further	far	ADV
fcis-2707	6	17	aggravates	aggravate	VERB
fcis-2707	6	18	the	the	DET
fcis-2707	6	19	counting	counting	NOUN
fcis-2707	6	20	error	error	NOUN
fcis-2707	6	21	.	.	PUNCT
fcis-2707	7	1	therefore	therefore	ADV
fcis-2707	7	2	,	,	PUNCT
fcis-2707	7	3	we	we	PRON
fcis-2707	7	4	propose	propose	VERB
fcis-2707	7	5	a	a	DET
fcis-2707	7	6	dual	dual	ADJ
fcis-2707	7	7	-	-	PUNCT
fcis-2707	7	8	track	track	NOUN
fcis-2707	7	9	attention	attention	NOUN
fcis-2707	7	10	network	network	NOUN
fcis-2707	7	11	that	that	PRON
fcis-2707	7	12	distinguishes	distinguish	VERB
fcis-2707	7	13	between	between	ADP
fcis-2707	7	14	global	global	ADJ
fcis-2707	7	15	and	and	CCONJ
fcis-2707	7	16	local	local	ADJ
fcis-2707	7	17	information	information	NOUN
fcis-2707	7	18	,	,	PUNCT
fcis-2707	7	19	which	which	PRON
fcis-2707	7	20	is	be	AUX
fcis-2707	7	21	responsible	responsible	ADJ
fcis-2707	7	22	for	for	ADP
fcis-2707	7	23	the	the	DET
fcis-2707	7	24	target	target	NOUN
fcis-2707	7	25	overlap	overlap	NOUN
fcis-2707	7	26	and	and	CCONJ
fcis-2707	7	27	background	background	NOUN
fcis-2707	7	28	confusion	confusion	NOUN
fcis-2707	7	29	problems	problem	NOUN
fcis-2707	7	30	,	,	PUNCT
fcis-2707	7	31	respectively	respectively	ADV
fcis-2707	7	32	,	,	PUNCT
fcis-2707	7	33	and	and	CCONJ
fcis-2707	7	34	finally	finally	ADV
fcis-2707	7	35	converges	converge	VERB
fcis-2707	7	36	and	and	CCONJ
fcis-2707	7	37	normalizes	normalize	VERB
fcis-2707	7	38	with	with	ADP
fcis-2707	7	39	the	the	DET
fcis-2707	7	40	feature	feature	NOUN
fcis-2707	7	41	map	map	NOUN
fcis-2707	7	42	to	to	PART
fcis-2707	7	43	transform	transform	VERB
fcis-2707	7	44	the	the	DET
fcis-2707	7	45	multi	multi	ADJ
fcis-2707	7	46	-	-	ADJ
fcis-2707	7	47	channel	channel	ADJ
fcis-2707	7	48	attention	attention	NOUN
fcis-2707	7	49	map	map	NOUN
fcis-2707	7	50	into	into	ADP
fcis-2707	7	51	a	a	DET
fcis-2707	7	52	single	single	ADJ
fcis-2707	7	53	-	-	PUNCT
fcis-2707	7	54	channel	channel	NOUN
fcis-2707	7	55	density	density	NOUN
fcis-2707	7	56	map	map	NOUN
fcis-2707	7	57	.	.	PUNCT
fcis-2707	8	1	meanwhile	meanwhile	ADV
fcis-2707	8	2	the	the	DET
fcis-2707	8	3	heterogeneous	heterogeneous	ADJ
fcis-2707	8	4	pyramid	pyramid	NOUN
fcis-2707	8	5	design	design	NOUN
fcis-2707	8	6	alleviates	alleviate	VERB
fcis-2707	8	7	the	the	DET
fcis-2707	8	8	distress	distress	NOUN
fcis-2707	8	9	of	of	ADP
fcis-2707	8	10	scale	scale	NOUN
fcis-2707	8	11	variation	variation	NOUN
fcis-2707	8	12	and	and	CCONJ
fcis-2707	8	13	density	density	NOUN
fcis-2707	8	14	dissimilarity	dissimilarity	NOUN
fcis-2707	8	15	.	.	PUNCT
fcis-2707	9	1	experiments	experiment	NOUN
fcis-2707	9	2	on	on	ADP
fcis-2707	9	3	several	several	ADJ
fcis-2707	9	4	official	official	ADJ
fcis-2707	9	5	datasets	dataset	NOUN
fcis-2707	9	6	prove	prove	VERB
fcis-2707	9	7	the	the	DET
fcis-2707	9	8	effectiveness	effectiveness	NOUN
fcis-2707	9	9	of	of	ADP
fcis-2707	9	10	the	the	DET
fcis-2707	9	11	scheme	scheme	NOUN
fcis-2707	9	12	to	to	PART
fcis-2707	9	13	enhance	enhance	VERB
fcis-2707	9	14	key	key	ADJ
fcis-2707	9	15	information	information	NOUN
fcis-2707	9	16	and	and	CCONJ
fcis-2707	9	17	overcome	overcome	VERB
fcis-2707	9	18	confounding	confound	VERB
fcis-2707	9	19	factors	factor	NOUN
fcis-2707	9	20	.	.	PUNCT
fcis-2707	10	1	keywords	keyword	NOUN
fcis-2707	10	2	:	:	PUNCT
fcis-2707	10	3	crowd	crowd	NOUN
fcis-2707	10	4	counting	counting	NOUN
fcis-2707	10	5	;	;	PUNCT
fcis-2707	10	6	attention	attention	NOUN
fcis-2707	10	7	fusion	fusion	NOUN
fcis-2707	10	8	;	;	PUNCT
fcis-2707	10	9	softmax	softmax	NOUN
fcis-2707	10	10	algorithm	algorithm	NOUN
fcis-2707	10	11	;	;	PUNCT
fcis-2707	10	12	density	density	NOUN
fcis-2707	10	13	map	map	NOUN
fcis-2707	10	14	.	.	PUNCT
fcis-2707	11	1	1	1	X
fcis-2707	11	2	.	.	X
fcis-2707	11	3	introduction	introduction	NOUN
fcis-2707	11	4	dense	dense	ADJ
fcis-2707	11	5	crowd	crowd	NOUN
fcis-2707	11	6	counting	counting	NOUN
fcis-2707	11	7	is	be	AUX
fcis-2707	11	8	defined	define	VERB
fcis-2707	11	9	as	as	ADP
fcis-2707	11	10	estimating	estimate	VERB
fcis-2707	11	11	the	the	DET
fcis-2707	11	12	number	number	NOUN
fcis-2707	11	13	of	of	ADP
fcis-2707	11	14	people	people	NOUN
fcis-2707	11	15	in	in	ADP
fcis-2707	11	16	an	an	DET
fcis-2707	11	17	image	image	NOUN
fcis-2707	11	18	or	or	CCONJ
fcis-2707	11	19	video	video	NOUN
fcis-2707	11	20	clip	clip	NOUN
fcis-2707	11	21	,	,	PUNCT
fcis-2707	11	22	generally	generally	ADV
fcis-2707	11	23	using	use	VERB
fcis-2707	11	24	heads	head	NOUN
fcis-2707	11	25	as	as	ADP
fcis-2707	11	26	the	the	DET
fcis-2707	11	27	counting	counting	NOUN
fcis-2707	11	28	unit	unit	NOUN
fcis-2707	11	29	.	.	PUNCT
fcis-2707	12	1	in	in	ADP
fcis-2707	12	2	the	the	DET
fcis-2707	12	3	density	density	NOUN
fcis-2707	12	4	map	map	NOUN
fcis-2707	12	5	estimation	estimation	NOUN
fcis-2707	12	6	strategy	strategy	NOUN
fcis-2707	12	7	,	,	PUNCT
fcis-2707	12	8	each	each	DET
fcis-2707	12	9	pixel	pixel	NOUN
fcis-2707	12	10	point	point	NOUN
fcis-2707	12	11	represents	represent	VERB
fcis-2707	12	12	the	the	DET
fcis-2707	12	13	probability	probability	NOUN
fcis-2707	12	14	of	of	ADP
fcis-2707	12	15	this	this	DET
fcis-2707	12	16	location	location	NOUN
fcis-2707	12	17	being	be	AUX
fcis-2707	12	18	the	the	DET
fcis-2707	12	19	center	center	NOUN
fcis-2707	12	20	of	of	ADP
fcis-2707	12	21	the	the	DET
fcis-2707	12	22	head	head	NOUN
fcis-2707	12	23	,	,	PUNCT
fcis-2707	12	24	thus	thus	ADV
fcis-2707	12	25	reducing	reduce	VERB
fcis-2707	12	26	the	the	DET
fcis-2707	12	27	counting	counting	NOUN
fcis-2707	12	28	task	task	NOUN
fcis-2707	12	29	to	to	ADP
fcis-2707	12	30	the	the	DET
fcis-2707	12	31	accumulation	accumulation	NOUN
fcis-2707	12	32	of	of	ADP
fcis-2707	12	33	probabilities	probability	NOUN
fcis-2707	12	34	.	.	PUNCT
fcis-2707	13	1	however	however	ADV
fcis-2707	13	2	,	,	PUNCT
fcis-2707	13	3	in	in	ADP
fcis-2707	13	4	real	real	ADJ
fcis-2707	13	5	scenarios	scenario	NOUN
fcis-2707	13	6	,	,	PUNCT
fcis-2707	13	7	a	a	DET
fcis-2707	13	8	robust	robust	ADJ
fcis-2707	13	9	counting	counting	NOUN
fcis-2707	13	10	model	model	NOUN
fcis-2707	13	11	requires	require	VERB
fcis-2707	13	12	strong	strong	ADJ
fcis-2707	13	13	generalization	generalization	NOUN
fcis-2707	13	14	ability	ability	NOUN
fcis-2707	13	15	to	to	ADP
fcis-2707	13	16	external	external	ADJ
fcis-2707	13	17	disturbances	disturbance	NOUN
fcis-2707	13	18	such	such	ADJ
fcis-2707	13	19	as	as	ADP
fcis-2707	13	20	noisy	noisy	ADJ
fcis-2707	13	21	background	background	NOUN
fcis-2707	13	22	,	,	PUNCT
fcis-2707	13	23	scale	scale	NOUN
fcis-2707	13	24	variation	variation	NOUN
fcis-2707	13	25	,	,	PUNCT
fcis-2707	13	26	mutual	mutual	ADJ
fcis-2707	13	27	occlusion	occlusion	NOUN
fcis-2707	13	28	,	,	PUNCT
fcis-2707	13	29	perspective	perspective	NOUN
fcis-2707	13	30	distortion	distortion	NOUN
fcis-2707	13	31	,	,	PUNCT
fcis-2707	13	32	etc	etc	X
fcis-2707	13	33	.	.	X
fcis-2707	13	34	traditional	traditional	ADJ
fcis-2707	13	35	counting	counting	NOUN
fcis-2707	13	36	networks	network	NOUN
fcis-2707	13	37	rely	rely	VERB
fcis-2707	13	38	on	on	ADP
fcis-2707	13	39	multi	multi	ADJ
fcis-2707	13	40	-	-	ADJ
fcis-2707	13	41	column	column	ADJ
fcis-2707	13	42	architectures	architecture	NOUN
fcis-2707	13	43	to	to	PART
fcis-2707	13	44	extract	extract	VERB
fcis-2707	13	45	features	feature	NOUN
fcis-2707	13	46	at	at	ADP
fcis-2707	13	47	different	different	ADJ
fcis-2707	13	48	scales	scale	NOUN
fcis-2707	13	49	while	while	SCONJ
fcis-2707	13	50	focusing	focus	VERB
fcis-2707	13	51	on	on	ADP
fcis-2707	13	52	valuable	valuable	ADJ
fcis-2707	13	53	visual	visual	ADJ
fcis-2707	13	54	information	information	NOUN
fcis-2707	13	55	based	base	VERB
fcis-2707	13	56	on	on	ADP
fcis-2707	13	57	attention	attention	NOUN
fcis-2707	13	58	mechanisms	mechanism	NOUN
fcis-2707	13	59	.	.	PUNCT
fcis-2707	14	1	1.1	1.1	NUM
fcis-2707	14	2	.	.	PUNCT
fcis-2707	15	1	multi	multi	ADJ
fcis-2707	15	2	-	-	ADJ
fcis-2707	15	3	scale	scale	ADJ
fcis-2707	15	4	feature	feature	NOUN
fcis-2707	15	5	extraction	extraction	NOUN
fcis-2707	15	6	strategy	strategy	NOUN
fcis-2707	15	7	this	this	DET
fcis-2707	15	8	strategy	strategy	NOUN
fcis-2707	15	9	emphasizes	emphasize	VERB
fcis-2707	15	10	that	that	SCONJ
fcis-2707	15	11	targets	target	NOUN
fcis-2707	15	12	at	at	ADP
fcis-2707	15	13	different	different	ADJ
fcis-2707	15	14	scales	scale	NOUN
fcis-2707	15	15	need	need	VERB
fcis-2707	15	16	to	to	PART
fcis-2707	15	17	be	be	AUX
fcis-2707	15	18	perceived	perceive	VERB
fcis-2707	15	19	by	by	ADP
fcis-2707	15	20	perceptual	perceptual	ADJ
fcis-2707	15	21	fields	field	NOUN
fcis-2707	15	22	of	of	ADP
fcis-2707	15	23	different	different	ADJ
fcis-2707	15	24	sizes	size	NOUN
fcis-2707	15	25	,	,	PUNCT
fcis-2707	15	26	which	which	PRON
fcis-2707	15	27	is	be	AUX
fcis-2707	15	28	generally	generally	ADV
fcis-2707	15	29	implemented	implement	VERB
fcis-2707	15	30	using	use	VERB
fcis-2707	15	31	a	a	DET
fcis-2707	15	32	multi	multi	ADJ
fcis-2707	15	33	-	-	ADJ
fcis-2707	15	34	column	column	ADJ
fcis-2707	15	35	convolutional	convolutional	ADJ
fcis-2707	15	36	architecture	architecture	NOUN
fcis-2707	15	37	.	.	PUNCT
fcis-2707	16	1	mcnn	mcnn	NOUN
fcis-2707	17	1	[	[	X
fcis-2707	17	2	1	1	X
fcis-2707	17	3	]	]	PUNCT
fcis-2707	17	4	first	first	ADV
fcis-2707	17	5	uses	use	VERB
fcis-2707	17	6	a	a	DET
fcis-2707	17	7	threecolumn	threecolumn	NOUN
fcis-2707	17	8	network	network	NOUN
fcis-2707	17	9	architecture	architecture	NOUN
fcis-2707	17	10	to	to	PART
fcis-2707	17	11	extract	extract	VERB
fcis-2707	17	12	multi	multi	ADJ
fcis-2707	17	13	-	-	ADJ
fcis-2707	17	14	scale	scale	ADJ
fcis-2707	17	15	features	feature	NOUN
fcis-2707	17	16	to	to	PART
fcis-2707	17	17	accommodate	accommodate	VERB
fcis-2707	17	18	scale	scale	NOUN
fcis-2707	17	19	variations	variation	NOUN
fcis-2707	17	20	due	due	ADJ
fcis-2707	17	21	to	to	ADP
fcis-2707	17	22	different	different	ADJ
fcis-2707	17	23	camera	camera	NOUN
fcis-2707	17	24	angles	angle	NOUN
fcis-2707	17	25	.	.	PUNCT
fcis-2707	18	1	inspired	inspire	VERB
fcis-2707	18	2	by	by	ADP
fcis-2707	18	3	mcnn	mcnn	NOUN
fcis-2707	18	4	[	[	X
fcis-2707	18	5	1	1	NUM
fcis-2707	18	6	]	]	PUNCT
fcis-2707	18	7	,	,	PUNCT
fcis-2707	18	8	switching	switch	VERB
fcis-2707	18	9	-	-	PUNCT
fcis-2707	18	10	cnn	cnn	NOUN
fcis-2707	18	11	[	[	X
fcis-2707	18	12	2	2	NUM
fcis-2707	18	13	]	]	PUNCT
fcis-2707	18	14	retains	retain	VERB
fcis-2707	18	15	the	the	DET
fcis-2707	18	16	multicolumn	multicolumn	PROPN
fcis-2707	18	17	mode	mode	NOUN
fcis-2707	18	18	,	,	PUNCT
fcis-2707	18	19	adds	add	VERB
fcis-2707	18	20	a	a	DET
fcis-2707	18	21	classifier	classifier	NOUN
fcis-2707	18	22	to	to	PART
fcis-2707	18	23	select	select	VERB
fcis-2707	18	24	the	the	DET
fcis-2707	18	25	best	good	ADJ
fcis-2707	18	26	branch	branch	NOUN
fcis-2707	18	27	suitable	suitable	ADJ
fcis-2707	18	28	for	for	ADP
fcis-2707	18	29	the	the	DET
fcis-2707	18	30	current	current	ADJ
fcis-2707	18	31	scale	scale	NOUN
fcis-2707	18	32	,	,	PUNCT
fcis-2707	18	33	and	and	CCONJ
fcis-2707	18	34	then	then	ADV
fcis-2707	18	35	adaptively	adaptively	ADV
fcis-2707	18	36	fuse	fuse	VERB
fcis-2707	18	37	the	the	DET
fcis-2707	18	38	multi	multi	ADJ
fcis-2707	18	39	-	-	ADJ
fcis-2707	18	40	scale	scale	ADJ
fcis-2707	18	41	information	information	NOUN
fcis-2707	18	42	.	.	PUNCT
fcis-2707	19	1	further	far	ADV
fcis-2707	19	2	,	,	PUNCT
fcis-2707	19	3	csrnet	csrnet	NOUN
fcis-2707	19	4	[	[	X
fcis-2707	19	5	3	3	NUM
fcis-2707	19	6	]	]	PUNCT
fcis-2707	19	7	adapts	adapt	VERB
fcis-2707	19	8	a	a	DET
fcis-2707	19	9	dilated	dilated	ADJ
fcis-2707	19	10	convolutional	convolutional	ADJ
fcis-2707	19	11	layer	layer	NOUN
fcis-2707	19	12	to	to	PART
fcis-2707	19	13	increase	increase	VERB
fcis-2707	19	14	the	the	DET
fcis-2707	19	15	receptive	receptive	ADJ
fcis-2707	19	16	field	field	NOUN
fcis-2707	19	17	as	as	ADP
fcis-2707	19	18	an	an	DET
fcis-2707	19	19	alternative	alternative	NOUN
fcis-2707	19	20	to	to	ADP
fcis-2707	19	21	the	the	DET
fcis-2707	19	22	pooling	pool	VERB
fcis-2707	19	23	operations	operation	NOUN
fcis-2707	19	24	,	,	PUNCT
fcis-2707	19	25	but	but	CCONJ
fcis-2707	19	26	it	it	PRON
fcis-2707	19	27	tends	tend	VERB
fcis-2707	19	28	to	to	PART
fcis-2707	19	29	lead	lead	VERB
fcis-2707	19	30	to	to	ADP
fcis-2707	19	31	grid	grid	NOUN
fcis-2707	19	32	effects	effect	NOUN
fcis-2707	19	33	,	,	PUNCT
fcis-2707	19	34	further	far	ADV
fcis-2707	19	35	leading	lead	VERB
fcis-2707	19	36	to	to	ADP
fcis-2707	19	37	local	local	ADJ
fcis-2707	19	38	information	information	NOUN
fcis-2707	19	39	loss	loss	NOUN
fcis-2707	19	40	.	.	PUNCT
fcis-2707	20	1	sanet	sanet	NOUN
fcis-2707	20	2	[	[	X
fcis-2707	20	3	4	4	X
fcis-2707	20	4	]	]	PUNCT
fcis-2707	20	5	sets	set	VERB
fcis-2707	20	6	inception	inception	ADJ
fcis-2707	20	7	layout	layout	NOUN
fcis-2707	20	8	in	in	ADP
fcis-2707	20	9	the	the	DET
fcis-2707	20	10	encoder	encoder	NOUN
fcis-2707	20	11	to	to	PART
fcis-2707	20	12	extract	extract	VERB
fcis-2707	20	13	multi	multi	ADJ
fcis-2707	20	14	-	-	ADJ
fcis-2707	20	15	scale	scale	ADJ
fcis-2707	20	16	features	feature	NOUN
fcis-2707	20	17	and	and	CCONJ
fcis-2707	20	18	adds	add	VERB
fcis-2707	20	19	transposed	transpose	VERB
fcis-2707	20	20	convolution	convolution	NOUN
fcis-2707	20	21	in	in	ADP
fcis-2707	20	22	the	the	DET
fcis-2707	20	23	decoder	decoder	NOUN
fcis-2707	20	24	to	to	PART
fcis-2707	20	25	generate	generate	VERB
fcis-2707	20	26	high	high	ADJ
fcis-2707	20	27	-	-	PUNCT
fcis-2707	20	28	resolution	resolution	NOUN
fcis-2707	20	29	density	density	NOUN
fcis-2707	20	30	maps	map	NOUN
fcis-2707	20	31	.	.	PUNCT
fcis-2707	21	1	1.2	1.2	NUM
fcis-2707	21	2	.	.	PUNCT
fcis-2707	21	3	attention	attention	NOUN
fcis-2707	21	4	mechanism	mechanism	NOUN
fcis-2707	21	5	guidance	guidance	NOUN
fcis-2707	21	6	strategy	strategy	NOUN
fcis-2707	21	7	attention	attention	NOUN
fcis-2707	21	8	mechanism	mechanism	NOUN
fcis-2707	21	9	is	be	AUX
fcis-2707	21	10	activated	activate	VERB
fcis-2707	21	11	by	by	ADP
fcis-2707	21	12	the	the	DET
fcis-2707	21	13	sigmoid	sigmoid	NOUN
fcis-2707	21	14	function	function	NOUN
fcis-2707	21	15	,	,	PUNCT
fcis-2707	21	16	which	which	PRON
fcis-2707	21	17	directs	direct	VERB
fcis-2707	21	18	the	the	DET
fcis-2707	21	19	model	model	NOUN
fcis-2707	21	20	to	to	PART
fcis-2707	21	21	focus	focus	VERB
fcis-2707	21	22	on	on	ADP
fcis-2707	21	23	regions	region	NOUN
fcis-2707	21	24	where	where	SCONJ
fcis-2707	21	25	the	the	DET
fcis-2707	21	26	signal	signal	ADJ
fcis-2707	21	27	response	response	NOUN
fcis-2707	21	28	is	be	AUX
fcis-2707	21	29	obvious	obvious	ADJ
fcis-2707	21	30	and	and	CCONJ
fcis-2707	21	31	suppresses	suppress	VERB
fcis-2707	21	32	background	background	NOUN
fcis-2707	21	33	noise	noise	NOUN
fcis-2707	21	34	,	,	PUNCT
fcis-2707	21	35	thus	thus	ADV
fcis-2707	21	36	acting	act	VERB
fcis-2707	21	37	as	as	ADP
fcis-2707	21	38	a	a	DET
fcis-2707	21	39	top	top	ADJ
fcis-2707	21	40	-	-	PUNCT
fcis-2707	21	41	level	level	NOUN
fcis-2707	21	42	supervision	supervision	NOUN
fcis-2707	21	43	.	.	PUNCT
fcis-2707	22	1	asnet	asnet	NOUN
fcis-2707	23	1	[	[	X
fcis-2707	23	2	5	5	X
fcis-2707	23	3	]	]	PUNCT
fcis-2707	23	4	considers	consider	VERB
fcis-2707	23	5	the	the	DET
fcis-2707	23	6	density	density	NOUN
fcis-2707	23	7	of	of	ADP
fcis-2707	23	8	different	different	ADJ
fcis-2707	23	9	regions	region	NOUN
fcis-2707	23	10	in	in	ADP
fcis-2707	23	11	an	an	DET
fcis-2707	23	12	image	image	NOUN
fcis-2707	23	13	varies	vary	VERB
fcis-2707	23	14	greatly	greatly	ADV
fcis-2707	23	15	,	,	PUNCT
fcis-2707	23	16	leading	lead	VERB
fcis-2707	23	17	to	to	ADP
fcis-2707	23	18	heterogeneous	heterogeneous	ADJ
fcis-2707	23	19	counting	counting	NOUN
fcis-2707	23	20	performance	performance	NOUN
fcis-2707	23	21	,	,	PUNCT
fcis-2707	23	22	and	and	CCONJ
fcis-2707	23	23	therefore	therefore	ADV
fcis-2707	23	24	proposes	propose	VERB
fcis-2707	23	25	density	density	NOUN
fcis-2707	23	26	attention	attention	NOUN
fcis-2707	23	27	networks	network	NOUN
fcis-2707	23	28	to	to	PART
fcis-2707	23	29	provide	provide	VERB
fcis-2707	23	30	multi	multi	ADJ
fcis-2707	23	31	-	-	ADJ
fcis-2707	23	32	scale	scale	ADJ
fcis-2707	23	33	attention	attention	NOUN
fcis-2707	23	34	masks	mask	NOUN
fcis-2707	23	35	for	for	ADP
fcis-2707	23	36	convolutional	convolutional	ADJ
fcis-2707	23	37	extraction	extraction	NOUN
fcis-2707	23	38	units	unit	NOUN
fcis-2707	23	39	.	.	PUNCT
fcis-2707	24	1	hanet	hanet	PROPN
fcis-2707	25	1	[	[	X
fcis-2707	25	2	6	6	NUM
fcis-2707	25	3	]	]	PUNCT
fcis-2707	25	4	utilizes	utilize	VERB
fcis-2707	25	5	progressive	progressive	ADJ
fcis-2707	25	6	embedding	embed	VERB
fcis-2707	25	7	of	of	ADP
fcis-2707	25	8	scale	scale	NOUN
fcis-2707	25	9	-	-	PUNCT
fcis-2707	25	10	context	context	NOUN
fcis-2707	25	11	fusion	fusion	NOUN
fcis-2707	25	12	channel	channel	NOUN
fcis-2707	25	13	attention	attention	NOUN
fcis-2707	25	14	with	with	ADP
fcis-2707	25	15	spatial	spatial	ADJ
fcis-2707	25	16	attention	attention	NOUN
fcis-2707	25	17	,	,	PUNCT
fcis-2707	25	18	without	without	ADP
fcis-2707	25	19	considering	consider	VERB
fcis-2707	25	20	that	that	SCONJ
fcis-2707	25	21	there	there	PRON
fcis-2707	25	22	are	be	VERB
fcis-2707	25	23	differences	difference	NOUN
fcis-2707	25	24	in	in	ADP
fcis-2707	25	25	the	the	DET
fcis-2707	25	26	supervised	supervised	ADJ
fcis-2707	25	27	objects	object	NOUN
fcis-2707	25	28	of	of	ADP
fcis-2707	25	29	attention	attention	NOUN
fcis-2707	25	30	in	in	ADP
fcis-2707	25	31	the	the	DET
fcis-2707	25	32	local	local	ADJ
fcis-2707	25	33	and	and	CCONJ
fcis-2707	25	34	global	global	ADJ
fcis-2707	25	35	cases	case	NOUN
fcis-2707	25	36	.	.	PUNCT
fcis-2707	26	1	ranet	ranet	NOUN
fcis-2707	27	1	[	[	X
fcis-2707	27	2	7	7	NUM
fcis-2707	27	3	]	]	PUNCT
fcis-2707	27	4	emphasizes	emphasize	VERB
fcis-2707	27	5	on	on	ADP
fcis-2707	27	6	attention	attention	NOUN
fcis-2707	27	7	optimisation	optimisation	NOUN
fcis-2707	27	8	,	,	PUNCT
fcis-2707	27	9	using	use	VERB
fcis-2707	27	10	two	two	NUM
fcis-2707	27	11	modules	module	NOUN
fcis-2707	27	12	to	to	PART
fcis-2707	27	13	handle	handle	VERB
fcis-2707	27	14	global	global	ADJ
fcis-2707	27	15	attention	attention	NOUN
fcis-2707	27	16	and	and	CCONJ
fcis-2707	27	17	local	local	ADJ
fcis-2707	27	18	attention	attention	NOUN
fcis-2707	27	19	separately	separately	ADV
fcis-2707	27	20	,	,	PUNCT
fcis-2707	27	21	and	and	CCONJ
fcis-2707	27	22	then	then	ADV
fcis-2707	27	23	finally	finally	ADV
fcis-2707	27	24	fusing	fuse	VERB
fcis-2707	27	25	them	they	PRON
fcis-2707	27	26	based	base	VERB
fcis-2707	27	27	on	on	ADP
fcis-2707	27	28	the	the	DET
fcis-2707	27	29	interdependencies	interdependency	NOUN
fcis-2707	27	30	between	between	ADP
fcis-2707	27	31	features	feature	NOUN
fcis-2707	27	32	,	,	PUNCT
fcis-2707	27	33	but	but	CCONJ
fcis-2707	27	34	the	the	DET
fcis-2707	27	35	dependencies	dependency	NOUN
fcis-2707	27	36	are	be	AUX
fcis-2707	27	37	difficult	difficult	ADJ
fcis-2707	27	38	to	to	PART
fcis-2707	27	39	determine	determine	VERB
fcis-2707	27	40	.	.	PUNCT
fcis-2707	28	1	recognizing	recognize	VERB
fcis-2707	28	2	that	that	SCONJ
fcis-2707	28	3	it	it	PRON
fcis-2707	28	4	is	be	AUX
fcis-2707	28	5	often	often	ADV
fcis-2707	28	6	difficult	difficult	ADJ
fcis-2707	28	7	to	to	PART
fcis-2707	28	8	generate	generate	VERB
fcis-2707	28	9	accurate	accurate	ADJ
fcis-2707	28	10	attention	attention	NOUN
fcis-2707	28	11	maps	map	NOUN
fcis-2707	28	12	directly	directly	ADV
fcis-2707	28	13	,	,	PUNCT
fcis-2707	28	14	cfanet	cfanet	ADJ
fcis-2707	28	15	[	[	X
fcis-2707	28	16	8	8	NUM
fcis-2707	28	17	]	]	PUNCT
fcis-2707	28	18	turns	turn	VERB
fcis-2707	28	19	to	to	ADP
fcis-2707	28	20	a	a	DET
fcis-2707	28	21	coarse	coarse	NOUN
fcis-2707	28	22	-	-	PUNCT
fcis-2707	28	23	to	to	ADP
fcis-2707	28	24	-	-	PUNCT
fcis-2707	28	25	fine	fine	ADJ
fcis-2707	28	26	progressive	progressive	ADJ
fcis-2707	28	27	attention	attention	NOUN
fcis-2707	28	28	mechanism	mechanism	NOUN
fcis-2707	28	29	through	through	ADP
fcis-2707	28	30	two	two	NUM
fcis-2707	28	31	branches	branch	NOUN
fcis-2707	28	32	,	,	PUNCT
fcis-2707	28	33	the	the	DET
fcis-2707	28	34	crowd	crowd	NOUN
fcis-2707	28	35	region	region	NOUN
fcis-2707	28	36	identifier	identifier	NOUN
fcis-2707	28	37	(	(	PUNCT
fcis-2707	28	38	crr	crr	PROPN
fcis-2707	28	39	)	)	PUNCT
fcis-2707	28	40	and	and	CCONJ
fcis-2707	28	41	the	the	DET
fcis-2707	28	42	density	density	NOUN
fcis-2707	28	43	level	level	NOUN
fcis-2707	28	44	estimator	estimator	NOUN
fcis-2707	28	45	(	(	PUNCT
fcis-2707	28	46	dle	dle	PROPN
fcis-2707	28	47	)	)	PUNCT
fcis-2707	28	48	.	.	PUNCT
fcis-2707	29	1	2	2	X
fcis-2707	29	2	.	.	NUM
fcis-2707	29	3	proposed	propose	VERB
fcis-2707	29	4	method	method	NOUN
fcis-2707	29	5	2.1	2.1	NUM
fcis-2707	29	6	.	.	PUNCT
fcis-2707	30	1	the	the	DET
fcis-2707	30	2	main	main	ADJ
fcis-2707	30	3	network	network	NOUN
fcis-2707	30	4	structure	structure	NOUN
fcis-2707	30	5	this	this	DET
fcis-2707	30	6	paper	paper	NOUN
fcis-2707	30	7	aims	aim	VERB
fcis-2707	30	8	to	to	PART
fcis-2707	30	9	establish	establish	VERB
fcis-2707	30	10	a	a	DET
fcis-2707	30	11	crowd	crowd	NOUN
fcis-2707	30	12	counting	count	VERB
fcis-2707	30	13	framework	framework	NOUN
fcis-2707	30	14	that	that	PRON
fcis-2707	30	15	is	be	AUX
fcis-2707	30	16	suitable	suitable	ADJ
fcis-2707	30	17	for	for	ADP
fcis-2707	30	18	dense	dense	ADJ
fcis-2707	30	19	scenes	scene	NOUN
fcis-2707	30	20	.	.	PUNCT
fcis-2707	31	1	the	the	DET
fcis-2707	31	2	architecture	architecture	NOUN
fcis-2707	31	3	of	of	ADP
fcis-2707	31	4	the	the	DET
fcis-2707	31	5	proposed	propose	VERB
fcis-2707	31	6	method	method	NOUN
fcis-2707	31	7	is	be	AUX
fcis-2707	31	8	illustrated	illustrate	VERB
fcis-2707	31	9	in	in	ADP
fcis-2707	31	10	figure	figure	NOUN
fcis-2707	31	11	1	1	NUM
fcis-2707	31	12	.	.	PUNCT
fcis-2707	32	1	it	it	PRON
fcis-2707	32	2	includes	include	VERB
fcis-2707	32	3	a	a	DET
fcis-2707	32	4	primary	primary	ADJ
fcis-2707	32	5	feature	feature	NOUN
fcis-2707	32	6	extractor	extractor	NOUN
fcis-2707	32	7	taken	take	VERB
fcis-2707	32	8	from	from	ADP
fcis-2707	32	9	the	the	DET
fcis-2707	32	10	vgg-16	vgg-16	NOUN
fcis-2707	32	11	[	[	X
fcis-2707	32	12	9	9	NUM
fcis-2707	32	13	]	]	PUNCT
fcis-2707	32	14	model	model	NOUN
fcis-2707	32	15	as	as	ADP
fcis-2707	32	16	the	the	DET
fcis-2707	32	17	backbone	backbone	NOUN
fcis-2707	32	18	,	,	PUNCT
fcis-2707	32	19	two	two	NUM
fcis-2707	32	20	heterogeneous	heterogeneous	ADJ
fcis-2707	32	21	pyramid	pyramid	NOUN
fcis-2707	32	22	modules	module	NOUN
fcis-2707	32	23	acting	act	VERB
fcis-2707	32	24	on	on	ADP
fcis-2707	32	25	global	global	ADJ
fcis-2707	32	26	and	and	CCONJ
fcis-2707	32	27	local	local	ADJ
fcis-2707	32	28	information	information	NOUN
fcis-2707	32	29	encoding	encoding	NOUN
fcis-2707	32	30	,	,	PUNCT
fcis-2707	32	31	respectively	respectively	ADV
fcis-2707	32	32	,	,	PUNCT
fcis-2707	32	33	and	and	CCONJ
fcis-2707	32	34	dual	dual	ADJ
fcis-2707	32	35	-	-	PUNCT
fcis-2707	32	36	track	track	NOUN
fcis-2707	32	37	stacking	stacking	NOUN
fcis-2707	32	38	to	to	PART
fcis-2707	32	39	obtain	obtain	VERB
fcis-2707	32	40	the	the	DET
fcis-2707	32	41	hybrid	hybrid	NOUN
fcis-2707	32	42	features	feature	NOUN
fcis-2707	32	43	,	,	PUNCT
fcis-2707	32	44	activated	activate	VERB
fcis-2707	32	45	to	to	PART
fcis-2707	32	46	get	get	VERB
fcis-2707	32	47	attention	attention	NOUN
fcis-2707	32	48	and	and	CCONJ
fcis-2707	32	49	then	then	ADV
fcis-2707	32	50	fused	fuse	VERB
fcis-2707	32	51	with	with	ADP
fcis-2707	32	52	the	the	DET
fcis-2707	32	53	multi	multi	ADJ
fcis-2707	32	54	-	-	ADJ
fcis-2707	32	55	channel	channel	ADJ
fcis-2707	32	56	feature	feature	NOUN
fcis-2707	32	57	map	map	NOUN
fcis-2707	32	58	to	to	PART
fcis-2707	32	59	obtain	obtain	VERB
fcis-2707	32	60	the	the	DET
fcis-2707	32	61	final	final	ADJ
fcis-2707	32	62	predicted	predict	VERB
fcis-2707	32	63	density	density	NOUN
fcis-2707	32	64	map	map	NOUN
fcis-2707	32	65	.	.	PUNCT
fcis-2707	33	1	the	the	DET
fcis-2707	33	2	local	local	ADJ
fcis-2707	33	3	information	information	NOUN
fcis-2707	33	4	encoding	encoding	NOUN
fcis-2707	33	5	stage	stage	NOUN
fcis-2707	33	6	is	be	AUX
fcis-2707	33	7	a	a	DET
fcis-2707	33	8	shallow	shallow	ADJ
fcis-2707	33	9	network	network	NOUN
fcis-2707	33	10	,	,	PUNCT
fcis-2707	33	11	capable	capable	ADJ
fcis-2707	33	12	of	of	ADP
fcis-2707	33	13	exploiting	exploit	VERB
fcis-2707	33	14	more	more	ADJ
fcis-2707	33	15	fine	fine	ADV
fcis-2707	33	16	-	-	PUNCT
fcis-2707	33	17	grained	grain	VERB
fcis-2707	33	18	feature	feature	NOUN
fcis-2707	33	19	information	information	NOUN
fcis-2707	33	20	and	and	CCONJ
fcis-2707	33	21	thus	thus	ADV
fcis-2707	33	22	filtering	filter	VERB
fcis-2707	33	23	complex	complex	ADJ
fcis-2707	33	24	backgrounds	background	NOUN
fcis-2707	33	25	with	with	ADP
fcis-2707	33	26	other	other	ADJ
fcis-2707	33	27	non	non	ADJ
fcis-2707	33	28	-	-	ADJ
fcis-2707	33	29	target	target	ADJ
fcis-2707	33	30	entities	entity	NOUN
fcis-2707	33	31	.	.	PUNCT
fcis-2707	34	1	a	a	DET
fcis-2707	34	2	four	four	NUM
fcis-2707	34	3	-	-	PUNCT
fcis-2707	34	4	branch	branch	NOUN
fcis-2707	34	5	pyramidal	pyramidal	ADJ
fcis-2707	34	6	architecture	architecture	NOUN
fcis-2707	34	7	is	be	AUX
fcis-2707	34	8	specifically	specifically	ADV
fcis-2707	34	9	used	use	VERB
fcis-2707	34	10	,	,	PUNCT
fcis-2707	34	11	with	with	ADP
fcis-2707	34	12	increasing	increase	VERB
fcis-2707	34	13	convolutional	convolutional	ADJ
fcis-2707	34	14	kernel	kernel	NOUN
fcis-2707	34	15	size	size	NOUN
fcis-2707	34	16	from	from	ADP
fcis-2707	34	17	top	top	NOUN
fcis-2707	34	18	to	to	ADP
fcis-2707	34	19	bottom	bottom	NOUN
fcis-2707	34	20	and	and	CCONJ
fcis-2707	34	21	progressively	progressively	ADV
fcis-2707	34	22	larger	large	ADJ
fcis-2707	34	23	perceptual	perceptual	ADJ
fcis-2707	34	24	fields	field	NOUN
fcis-2707	34	25	.	.	PUNCT
fcis-2707	35	1	the	the	DET
fcis-2707	35	2	global	global	ADJ
fcis-2707	35	3	information	information	NOUN
fcis-2707	35	4	encoding	encoding	NOUN
fcis-2707	35	5	stage	stage	NOUN
fcis-2707	35	6	has	have	VERB
fcis-2707	35	7	a	a	DET
fcis-2707	35	8	deeper	deep	ADJ
fcis-2707	35	9	layer	layer	NOUN
fcis-2707	35	10	of	of	ADP
fcis-2707	35	11	network	network	NOUN
fcis-2707	35	12	with	with	ADP
fcis-2707	35	13	enhanced	enhanced	ADJ
fcis-2707	35	14	nonlinearity	nonlinearity	NOUN
fcis-2707	35	15	,	,	PUNCT
fcis-2707	35	16	fuller	full	ADJ
fcis-2707	35	17	perceptual	perceptual	ADJ
fcis-2707	35	18	field	field	NOUN
fcis-2707	35	19	,	,	PUNCT
fcis-2707	35	20	and	and	CCONJ
fcis-2707	35	21	richer	rich	ADJ
fcis-2707	35	22	semantic	semantic	ADJ
fcis-2707	35	23	information	information	NOUN
fcis-2707	35	24	.	.	PUNCT
fcis-2707	36	1	it	it	PRON
fcis-2707	36	2	is	be	AUX
fcis-2707	36	3	used	use	VERB
fcis-2707	36	4	to	to	PART
fcis-2707	36	5	deal	deal	VERB
fcis-2707	36	6	with	with	ADP
fcis-2707	36	7	the	the	DET
fcis-2707	36	8	dense	dense	ADJ
fcis-2707	36	9	occlusion	occlusion	NOUN
fcis-2707	36	10	of	of	ADP
fcis-2707	36	11	human	human	ADJ
fcis-2707	36	12	head	head	NOUN
fcis-2707	36	13	and	and	CCONJ
fcis-2707	36	14	has	have	VERB
fcis-2707	36	15	good	good	ADJ
fcis-2707	36	16	learning	learning	NOUN
fcis-2707	36	17	ability	ability	NOUN
fcis-2707	36	18	for	for	ADP
fcis-2707	36	19	irregular	irregular	ADJ
fcis-2707	36	20	density	density	NOUN
fcis-2707	36	21	distribution	distribution	NOUN
fcis-2707	36	22	as	as	ADV
fcis-2707	36	23	well	well	ADV
fcis-2707	36	24	.	.	PUNCT
fcis-2707	37	1	to	to	PART
fcis-2707	37	2	reduce	reduce	VERB
fcis-2707	37	3	the	the	DET
fcis-2707	37	4	parameter	parameter	NOUN
fcis-2707	37	5	overhead	overhead	ADV
fcis-2707	37	6	,	,	PUNCT
fcis-2707	37	7	a	a	DET
fcis-2707	37	8	three	three	NUM
fcis-2707	37	9	-	-	PUNCT
fcis-2707	37	10	way	way	NOUN
fcis-2707	37	11	merge	merge	NOUN
fcis-2707	37	12	is	be	AUX
fcis-2707	37	13	used	use	VERB
fcis-2707	37	14	,	,	PUNCT
fcis-2707	37	15	and	and	CCONJ
fcis-2707	37	16	the	the	DET
fcis-2707	37	17	filter	filter	NOUN
fcis-2707	37	18	size	size	NOUN
fcis-2707	37	19	is	be	AUX
fcis-2707	37	20	also	also	ADV
fcis-2707	37	21	chosen	choose	VERB
fcis-2707	37	22	among	among	ADP
fcis-2707	37	23	1	1	NUM
fcis-2707	37	24	1	1	NUM
fcis-2707	37	25	,	,	PUNCT
fcis-2707	37	26	3	3	NUM
fcis-2707	37	27	3	3	NUM
fcis-2707	37	28	,	,	PUNCT
fcis-2707	37	29	and	and	CCONJ
fcis-2707	37	30	5	5	NUM
fcis-2707	37	31	5	5	NUM
fcis-2707	37	32	.	.	PUNCT
fcis-2707	38	1	36	36	NUM
fcis-2707	38	2	figure	figure	NOUN
fcis-2707	38	3	1	1	NUM
fcis-2707	38	4	.	.	PUNCT
fcis-2707	38	5	overall	overall	ADJ
fcis-2707	38	6	architecture	architecture	NOUN
fcis-2707	38	7	of	of	ADP
fcis-2707	38	8	the	the	DET
fcis-2707	38	9	proposed	propose	VERB
fcis-2707	38	10	network	network	NOUN
fcis-2707	38	11	the	the	DET
fcis-2707	38	12	dual	dual	ADJ
fcis-2707	38	13	-	-	PUNCT
fcis-2707	38	14	track	track	NOUN
fcis-2707	38	15	features	feature	NOUN
fcis-2707	38	16	are	be	AUX
fcis-2707	38	17	merged	merge	VERB
fcis-2707	38	18	and	and	CCONJ
fcis-2707	38	19	split	split	VERB
fcis-2707	38	20	in	in	ADP
fcis-2707	38	21	two	two	NUM
fcis-2707	38	22	again	again	ADV
fcis-2707	38	23	.	.	PUNCT
fcis-2707	39	1	in	in	ADP
fcis-2707	39	2	the	the	DET
fcis-2707	39	3	top	top	ADJ
fcis-2707	39	4	-	-	PUNCT
fcis-2707	39	5	side	side	NOUN
fcis-2707	39	6	pathway	pathway	NOUN
fcis-2707	39	7	,	,	PUNCT
fcis-2707	39	8	the	the	DET
fcis-2707	39	9	probability	probability	NOUN
fcis-2707	39	10	distribution	distribution	NOUN
fcis-2707	39	11	between	between	ADP
fcis-2707	39	12	[	[	X
fcis-2707	39	13	0,1	0,1	NUM
fcis-2707	39	14	]	]	PUNCT
fcis-2707	39	15	is	be	AUX
fcis-2707	39	16	generated	generate	VERB
fcis-2707	39	17	via	via	ADP
fcis-2707	39	18	relu	relu	NOUN
fcis-2707	39	19	and	and	CCONJ
fcis-2707	39	20	sigmoid	sigmoid	NOUN
fcis-2707	39	21	activation	activation	NOUN
fcis-2707	39	22	functions	function	NOUN
fcis-2707	39	23	in	in	ADP
fcis-2707	39	24	turn	turn	NOUN
fcis-2707	39	25	,	,	PUNCT
fcis-2707	39	26	i.e.	i.e.	X
fcis-2707	39	27	,	,	PUNCT
fcis-2707	39	28	hybrid	hybrid	ADJ
fcis-2707	39	29	attention	attention	NOUN
fcis-2707	39	30	.	.	PUNCT
fcis-2707	40	1	and	and	CCONJ
fcis-2707	40	2	in	in	ADP
fcis-2707	40	3	the	the	DET
fcis-2707	40	4	bottom	bottom	ADJ
fcis-2707	40	5	-	-	PUNCT
fcis-2707	40	6	side	side	NOUN
fcis-2707	40	7	pathway	pathway	NOUN
fcis-2707	40	8	,	,	PUNCT
fcis-2707	40	9	two	two	NUM
fcis-2707	40	10	33	33	NUM
fcis-2707	40	11	convolution	convolution	NOUN
fcis-2707	40	12	kernels	kernel	NOUN
fcis-2707	40	13	are	be	AUX
fcis-2707	40	14	used	use	VERB
fcis-2707	40	15	to	to	PART
fcis-2707	40	16	reform	reform	VERB
fcis-2707	40	17	the	the	DET
fcis-2707	40	18	feature	feature	NOUN
fcis-2707	40	19	information	information	NOUN
fcis-2707	40	20	first	first	ADV
fcis-2707	40	21	,	,	PUNCT
fcis-2707	40	22	and	and	CCONJ
fcis-2707	40	23	then	then	ADV
fcis-2707	40	24	11	11	NUM
fcis-2707	40	25	convolution	convolution	NOUN
fcis-2707	40	26	is	be	AUX
fcis-2707	40	27	used	use	VERB
fcis-2707	40	28	to	to	PART
fcis-2707	40	29	adjust	adjust	VERB
fcis-2707	40	30	it	it	PRON
fcis-2707	40	31	to	to	ADP
fcis-2707	40	32	the	the	DET
fcis-2707	40	33	exact	exact	ADJ
fcis-2707	40	34	same	same	ADJ
fcis-2707	40	35	size	size	NOUN
fcis-2707	40	36	as	as	ADP
fcis-2707	40	37	the	the	DET
fcis-2707	40	38	hybrid	hybrid	ADJ
fcis-2707	40	39	attention	attention	NOUN
fcis-2707	40	40	,	,	PUNCT
fcis-2707	40	41	i.e.	i.e.	X
fcis-2707	40	42	,	,	PUNCT
fcis-2707	40	43	the	the	DET
fcis-2707	40	44	multichannel	multichannel	ADJ
fcis-2707	40	45	feature	feature	NOUN
fcis-2707	40	46	map	map	NOUN
fcis-2707	40	47	.	.	PUNCT
fcis-2707	41	1	for	for	ADP
fcis-2707	41	2	the	the	DET
fcis-2707	41	3	fusion	fusion	NOUN
fcis-2707	41	4	strategy	strategy	NOUN
fcis-2707	41	5	,	,	PUNCT
fcis-2707	41	6	we	we	PRON
fcis-2707	41	7	introduce	introduce	VERB
fcis-2707	41	8	the	the	DET
fcis-2707	41	9	softmax	softmax	NOUN
fcis-2707	41	10	function	function	NOUN
fcis-2707	41	11	,	,	PUNCT
fcis-2707	41	12	which	which	PRON
fcis-2707	41	13	converts	convert	VERB
fcis-2707	41	14	the	the	DET
fcis-2707	41	15	multi	multi	ADJ
fcis-2707	41	16	-	-	ADJ
fcis-2707	41	17	channel	channel	ADJ
fcis-2707	41	18	attention	attention	NOUN
fcis-2707	41	19	map	map	NOUN
fcis-2707	41	20	into	into	ADP
fcis-2707	41	21	a	a	DET
fcis-2707	41	22	single	single	ADJ
fcis-2707	41	23	-	-	PUNCT
fcis-2707	41	24	channel	channel	NOUN
fcis-2707	41	25	density	density	NOUN
fcis-2707	41	26	map	map	NOUN
fcis-2707	41	27	,	,	PUNCT
fcis-2707	41	28	a	a	DET
fcis-2707	41	29	move	move	NOUN
fcis-2707	41	30	that	that	PRON
fcis-2707	41	31	eliminates	eliminate	VERB
fcis-2707	41	32	the	the	DET
fcis-2707	41	33	need	need	NOUN
fcis-2707	41	34	for	for	SCONJ
fcis-2707	41	35	the	the	DET
fcis-2707	41	36	network	network	NOUN
fcis-2707	41	37	to	to	PART
fcis-2707	41	38	resort	resort	VERB
fcis-2707	41	39	to	to	ADP
fcis-2707	41	40	costly	costly	ADJ
fcis-2707	41	41	and	and	CCONJ
fcis-2707	41	42	poorly	poorly	ADV
fcis-2707	41	43	robust	robust	ADJ
fcis-2707	41	44	attention	attention	NOUN
fcis-2707	41	45	labels	label	NOUN
fcis-2707	41	46	.	.	PUNCT
fcis-2707	42	1	in	in	ADP
fcis-2707	42	2	detail	detail	NOUN
fcis-2707	42	3	,	,	PUNCT
fcis-2707	42	4	the	the	DET
fcis-2707	42	5	hybrid	hybrid	ADJ
fcis-2707	42	6	attention	attention	NOUN
fcis-2707	42	7	is	be	AUX
fcis-2707	42	8	normalized	normalize	VERB
fcis-2707	42	9	by	by	ADP
fcis-2707	42	10	softmax	softmax	NOUN
fcis-2707	42	11	and	and	CCONJ
fcis-2707	42	12	each	each	DET
fcis-2707	42	13	pixel	pixel	NOUN
fcis-2707	42	14	can	can	AUX
fcis-2707	42	15	learn	learn	VERB
fcis-2707	42	16	the	the	DET
fcis-2707	42	17	dynamic	dynamic	ADJ
fcis-2707	42	18	weight	weight	NOUN
fcis-2707	42	19	of	of	ADP
fcis-2707	42	20	this	this	DET
fcis-2707	42	21	location	location	NOUN
fcis-2707	42	22	in	in	ADP
fcis-2707	42	23	all	all	DET
fcis-2707	42	24	channel	channel	NOUN
fcis-2707	42	25	layers	layer	NOUN
fcis-2707	42	26	.	.	PUNCT
fcis-2707	43	1	then	then	ADV
fcis-2707	43	2	,	,	PUNCT
fcis-2707	43	3	it	it	PRON
fcis-2707	43	4	is	be	AUX
fcis-2707	43	5	multiplied	multiply	VERB
fcis-2707	43	6	with	with	ADP
fcis-2707	43	7	the	the	DET
fcis-2707	43	8	multi	multi	ADJ
fcis-2707	43	9	-	-	ADJ
fcis-2707	43	10	channel	channel	ADJ
fcis-2707	43	11	feature	feature	NOUN
fcis-2707	43	12	maps	map	NOUN
fcis-2707	43	13	pairwise	pairwise	NOUN
fcis-2707	43	14	,	,	PUNCT
fcis-2707	43	15	and	and	CCONJ
fcis-2707	43	16	finally	finally	ADV
fcis-2707	43	17	,	,	PUNCT
fcis-2707	43	18	all	all	DET
fcis-2707	43	19	channels	channel	NOUN
fcis-2707	43	20	are	be	AUX
fcis-2707	43	21	summed	sum	VERB
fcis-2707	43	22	vertically	vertically	ADV
fcis-2707	43	23	to	to	PART
fcis-2707	43	24	obtain	obtain	VERB
fcis-2707	43	25	the	the	DET
fcis-2707	43	26	final	final	ADJ
fcis-2707	43	27	prediction	prediction	NOUN
fcis-2707	43	28	map	map	NOUN
fcis-2707	43	29	of	of	ADP
fcis-2707	43	30	fused	fuse	VERB
fcis-2707	43	31	attention	attention	NOUN
fcis-2707	43	32	to	to	ADP
fcis-2707	43	33	features	feature	NOUN
fcis-2707	43	34	,	,	PUNCT
fcis-2707	43	35	denoted	denote	VERB
fcis-2707	43	36	by	by	ADP
fcis-2707	43	37	1	1	NUM
fcis-2707	43	38	h	h	NOUN
fcis-2707	43	39	w	w	PROPN
fcis-2707	43	40	pref	pref	PROPN
fcis-2707	43	41			PROPN
fcis-2707	43	42			NOUN
fcis-2707	43	43	.	.	PUNCT
fcis-2707	44	1	(	(	PUNCT
fcis-2707	44	2	)	)	PUNCT
fcis-2707	44	3	(	(	PUNCT
fcis-2707	44	4	)	)	PUNCT
fcis-2707	44	5	,	,	PUNCT
fcis-2707	44	6	,	,	PUNCT
fcis-2707	44	7	,	,	PUNCT
fcis-2707	44	8	1	1	NUM
fcis-2707	44	9	1	1	NUM
fcis-2707	44	10	1i	1i	NOUN
fcis-2707	44	11	j	j	PROPN
fcis-2707	44	12	c	c	AUX
fcis-2707	44	13	pre	pre	X
fcis-2707	45	1	att	att	PROPN
fcis-2707	45	2	mul	mul	PROPN
fcis-2707	46	1	k	k	PROPN
fcis-2707	47	1	i	i	PRON
fcis-2707	47	2	j	j	PROPN
fcis-2707	48	1	k	k	INTJ
fcis-2707	49	1	i	i	PRON
fcis-2707	49	2	h	h	NOUN
fcis-2707	50	1	f	f	PROPN
fcis-2707	50	2	softmax	softmax	PROPN
fcis-2707	51	1	f	f	PROPN
fcis-2707	51	2	f	f	PROPN
fcis-2707	51	3	j	j	PROPN
fcis-2707	51	4	w=	w=	PROPN
fcis-2707	51	5			NOUN
fcis-2707	51	6			NOUN
fcis-2707	51	7	=	=	PUNCT
fcis-2707	51	8			NOUN
fcis-2707	51	9			NUM
fcis-2707	51	10			NUM
fcis-2707	51	11			ADJ
fcis-2707	51	12			X
fcis-2707	51	13	(	(	PUNCT
fcis-2707	51	14	1	1	NUM
fcis-2707	51	15	)	)	PUNCT
fcis-2707	51	16	2.2	2.2	NUM
fcis-2707	51	17	.	.	PUNCT
fcis-2707	52	1	loss	loss	NOUN
fcis-2707	52	2	function	function	NOUN
fcis-2707	52	3	in	in	ADP
fcis-2707	52	4	this	this	DET
fcis-2707	52	5	paper	paper	NOUN
fcis-2707	52	6	,	,	PUNCT
fcis-2707	52	7	we	we	PRON
fcis-2707	52	8	choose	choose	VERB
fcis-2707	52	9	the	the	DET
fcis-2707	52	10	mean	mean	ADJ
fcis-2707	52	11	absolute	absolute	ADJ
fcis-2707	52	12	error	error	NOUN
fcis-2707	52	13	(	(	PUNCT
fcis-2707	52	14	mae	mae	PROPN
fcis-2707	52	15	)	)	PUNCT
fcis-2707	52	16	to	to	PART
fcis-2707	52	17	measure	measure	VERB
fcis-2707	52	18	the	the	DET
fcis-2707	52	19	pixel	pixel	ADJ
fcis-2707	52	20	-	-	PUNCT
fcis-2707	52	21	level	level	NOUN
fcis-2707	52	22	error	error	NOUN
fcis-2707	52	23	values	value	NOUN
fcis-2707	52	24	between	between	ADP
fcis-2707	52	25	the	the	DET
fcis-2707	52	26	final	final	ADJ
fcis-2707	52	27	prediction	prediction	NOUN
fcis-2707	52	28	map	map	NOUN
fcis-2707	52	29	and	and	CCONJ
fcis-2707	52	30	the	the	DET
fcis-2707	52	31	labels	label	NOUN
fcis-2707	52	32	,	,	PUNCT
fcis-2707	52	33	denoted	denote	VERB
fcis-2707	52	34	by	by	ADP
fcis-2707	52	35	prel	prel	NOUN
fcis-2707	52	36	.	.	PUNCT
fcis-2707	53	1	(	(	PUNCT
fcis-2707	53	2	)	)	PUNCT
fcis-2707	53	3	2	2	NUM
fcis-2707	53	4	2	2	NUM
fcis-2707	53	5	1	1	NUM
fcis-2707	53	6	1	1	NUM
fcis-2707	53	7	;	;	PUNCT
fcis-2707	53	8	n	n	CCONJ
fcis-2707	54	1	gt	gt	INTJ
fcis-2707	54	2	pre	pre	VERB
fcis-2707	55	1	i	i	PRON
fcis-2707	55	2	i	i	INTJ
fcis-2707	56	1	i	i	VERB
fcis-2707	56	2	l	l	VERB
fcis-2707	57	1	p	p	X
fcis-2707	57	2	x	x	X
fcis-2707	57	3	g	g	PROPN
fcis-2707	57	4	n	n	NOUN
fcis-2707	57	5	=	=	SYM
fcis-2707	57	6	=	=	SYM
fcis-2707	57	7			PROPN
fcis-2707	57	8	−	−	PUNCT
fcis-2707	57	9	(	(	PUNCT
fcis-2707	57	10	2	2	NUM
fcis-2707	57	11	)	)	PUNCT
fcis-2707	57	12	where	where	SCONJ
fcis-2707	57	13	n	n	PRON
fcis-2707	57	14	is	be	AUX
fcis-2707	57	15	the	the	DET
fcis-2707	57	16	number	number	NOUN
fcis-2707	57	17	of	of	ADP
fcis-2707	57	18	images	image	NOUN
fcis-2707	57	19	in	in	ADP
fcis-2707	57	20	a	a	DET
fcis-2707	57	21	training	training	NOUN
fcis-2707	57	22	batch	batch	NOUN
fcis-2707	57	23	,	,	PUNCT
fcis-2707	57	24	ix	ix	SCONJ
fcis-2707	57	25	denotes	denote	VERB
fcis-2707	57	26	the	the	DET
fcis-2707	57	27	current	current	ADJ
fcis-2707	57	28	training	training	NOUN
fcis-2707	57	29	image	image	NOUN
fcis-2707	57	30	,	,	PUNCT
fcis-2707	57	31			PROPN
fcis-2707	57	32	is	be	AUX
fcis-2707	57	33	a	a	DET
fcis-2707	57	34	set	set	NOUN
fcis-2707	57	35	of	of	ADP
fcis-2707	57	36	learnable	learnable	ADJ
fcis-2707	57	37	parameters	parameter	NOUN
fcis-2707	57	38	,	,	PUNCT
fcis-2707	57	39	so	so	CCONJ
fcis-2707	57	40	(	(	PUNCT
fcis-2707	57	41	;	;	PUNCT
fcis-2707	57	42	)	)	PUNCT
fcis-2707	57	43	ip	ip	NOUN
fcis-2707	57	44	x	x	NOUN
fcis-2707	57	45			NOUN
fcis-2707	57	46	represents	represent	VERB
fcis-2707	57	47	the	the	DET
fcis-2707	57	48	prediction	prediction	NOUN
fcis-2707	57	49	map	map	NOUN
fcis-2707	57	50	for	for	ADP
fcis-2707	57	51	it	it	PRON
fcis-2707	57	52	,	,	PUNCT
fcis-2707	57	53	and	and	CCONJ
fcis-2707	57	54	gt	gt	PROPN
fcis-2707	57	55	ig	ig	PROPN
fcis-2707	57	56	refers	refer	VERB
fcis-2707	57	57	to	to	ADP
fcis-2707	57	58	its	its	PRON
fcis-2707	57	59	ground	ground	NOUN
fcis-2707	57	60	-	-	PUNCT
fcis-2707	57	61	truth	truth	NOUN
fcis-2707	57	62	density	density	NOUN
fcis-2707	57	63	map	map	NOUN
fcis-2707	57	64	.	.	PUNCT
fcis-2707	58	1	3	3	X
fcis-2707	58	2	.	.	X
fcis-2707	58	3	experiments	experiment	NOUN
fcis-2707	58	4	and	and	CCONJ
fcis-2707	58	5	results	result	VERB
fcis-2707	58	6	analysis	analysis	NOUN
fcis-2707	58	7	3.1	3.1	NUM
fcis-2707	58	8	.	.	PUNCT
fcis-2707	59	1	experimental	experimental	ADJ
fcis-2707	59	2	detail	detail	NOUN
fcis-2707	59	3	to	to	PART
fcis-2707	59	4	ensure	ensure	VERB
fcis-2707	59	5	the	the	DET
fcis-2707	59	6	experimental	experimental	ADJ
fcis-2707	59	7	authority	authority	NOUN
fcis-2707	59	8	,	,	PUNCT
fcis-2707	59	9	four	four	NUM
fcis-2707	59	10	official	official	ADJ
fcis-2707	59	11	datasets	dataset	NOUN
fcis-2707	59	12	,	,	PUNCT
fcis-2707	59	13	shanghaitech(a&b	shanghaitech(a&b	NOUN
fcis-2707	59	14	)	)	PUNCT
fcis-2707	60	1	[	[	X
fcis-2707	60	2	1	1	NUM
fcis-2707	60	3	]	]	PUNCT
fcis-2707	60	4	,	,	PUNCT
fcis-2707	60	5	ucf_cc_50	ucf_cc_50	PROPN
fcis-2707	61	1	[	[	X
fcis-2707	61	2	10	10	NUM
fcis-2707	61	3	]	]	PUNCT
fcis-2707	61	4	,	,	PUNCT
fcis-2707	61	5	and	and	CCONJ
fcis-2707	61	6	ucf	ucf	PROPN
fcis-2707	61	7	-	-	PUNCT
fcis-2707	61	8	qnrf	qnrf	NOUN
fcis-2707	62	1	[	[	X
fcis-2707	62	2	11	11	NUM
fcis-2707	62	3	]	]	PUNCT
fcis-2707	62	4	,	,	PUNCT
fcis-2707	62	5	are	be	AUX
fcis-2707	62	6	used	use	VERB
fcis-2707	62	7	in	in	ADP
fcis-2707	62	8	this	this	DET
fcis-2707	62	9	paper	paper	NOUN
fcis-2707	62	10	.	.	PUNCT
fcis-2707	63	1	among	among	ADP
fcis-2707	63	2	them	they	PRON
fcis-2707	63	3	,	,	PUNCT
fcis-2707	63	4	the	the	DET
fcis-2707	63	5	ucf_cc_50	ucf_cc_50	NUM
fcis-2707	63	6	dataset	dataset	NOUN
fcis-2707	63	7	has	have	VERB
fcis-2707	63	8	a	a	DET
fcis-2707	63	9	limited	limited	ADJ
fcis-2707	63	10	number	number	NOUN
fcis-2707	63	11	of	of	ADP
fcis-2707	63	12	samples	sample	NOUN
fcis-2707	63	13	,	,	PUNCT
fcis-2707	63	14	and	and	CCONJ
fcis-2707	63	15	we	we	PRON
fcis-2707	63	16	follow	follow	VERB
fcis-2707	63	17	the	the	DET
fcis-2707	63	18	official	official	ADJ
fcis-2707	63	19	recommendation	recommendation	NOUN
fcis-2707	63	20	of	of	ADP
fcis-2707	63	21	5	5	NUM
fcis-2707	63	22	-	-	ADJ
fcis-2707	63	23	fold	fold	ADJ
fcis-2707	63	24	cross	cross	NOUN
fcis-2707	63	25	-	-	NOUN
fcis-2707	63	26	validation	validation	NOUN
fcis-2707	63	27	for	for	ADP
fcis-2707	63	28	testing	testing	NOUN
fcis-2707	63	29	.	.	PUNCT
fcis-2707	64	1	we	we	PRON
fcis-2707	64	2	generate	generate	VERB
fcis-2707	64	3	training	training	NOUN
fcis-2707	64	4	labels	label	NOUN
fcis-2707	64	5	by	by	ADP
fcis-2707	64	6	blurring	blur	VERB
fcis-2707	64	7	each	each	DET
fcis-2707	64	8	head	head	NOUN
fcis-2707	64	9	annotation	annotation	NOUN
fcis-2707	64	10	with	with	ADP
fcis-2707	64	11	a	a	DET
fcis-2707	64	12	gaussian	gaussian	ADJ
fcis-2707	64	13	function	function	NOUN
fcis-2707	64	14	.	.	PUNCT
fcis-2707	65	1	in	in	ADP
fcis-2707	65	2	detail	detail	NOUN
fcis-2707	65	3	,	,	PUNCT
fcis-2707	65	4	for	for	ADP
fcis-2707	65	5	crowdsparse	crowdsparse	NOUN
fcis-2707	65	6	datasets	dataset	NOUN
fcis-2707	65	7	,	,	PUNCT
fcis-2707	65	8	such	such	ADJ
fcis-2707	65	9	as	as	ADP
fcis-2707	65	10	shanghaitech	shanghaitech	NOUN
fcis-2707	65	11	part	part	NOUN
fcis-2707	65	12	b	b	NOUN
fcis-2707	65	13	,	,	PUNCT
fcis-2707	65	14	we	we	PRON
fcis-2707	65	15	use	use	VERB
fcis-2707	65	16	fixedsize	fixedsize	NOUN
fcis-2707	65	17	kernels	kernel	NOUN
fcis-2707	65	18	,	,	PUNCT
fcis-2707	65	19	while	while	SCONJ
fcis-2707	65	20	for	for	ADP
fcis-2707	65	21	other	other	ADJ
fcis-2707	65	22	datasets	dataset	NOUN
fcis-2707	65	23	with	with	ADP
fcis-2707	65	24	denser	dense	ADJ
fcis-2707	65	25	scenes	scene	NOUN
fcis-2707	65	26	,	,	PUNCT
fcis-2707	65	27	geometric	geometric	ADJ
fcis-2707	65	28	adaptive	adaptive	ADJ
fcis-2707	65	29	kernel	kernel	NOUN
fcis-2707	65	30	based	base	VERB
fcis-2707	65	31	on	on	ADP
fcis-2707	65	32	the	the	DET
fcis-2707	65	33	nearest	near	ADJ
fcis-2707	65	34	neighbor	neighbor	NOUN
fcis-2707	65	35	algorithm	algorithm	NOUN
fcis-2707	65	36	is	be	AUX
fcis-2707	65	37	utilized	utilize	VERB
fcis-2707	65	38	.	.	PUNCT
fcis-2707	66	1	except	except	SCONJ
fcis-2707	66	2	for	for	ADP
fcis-2707	66	3	primary	primary	ADJ
fcis-2707	66	4	feature	feature	NOUN
fcis-2707	66	5	extractor	extractor	NOUN
fcis-2707	66	6	,	,	PUNCT
fcis-2707	66	7	the	the	DET
fcis-2707	66	8	parameters	parameter	NOUN
fcis-2707	66	9	of	of	ADP
fcis-2707	66	10	the	the	DET
fcis-2707	66	11	subsequent	subsequent	ADJ
fcis-2707	66	12	layers	layer	NOUN
fcis-2707	66	13	are	be	AUX
fcis-2707	66	14	randomly	randomly	ADV
fcis-2707	66	15	initialized	initialize	VERB
fcis-2707	66	16	by	by	ADP
fcis-2707	66	17	a	a	DET
fcis-2707	66	18	gaussian	gaussian	ADJ
fcis-2707	66	19	distribution	distribution	NOUN
fcis-2707	66	20	with	with	ADP
fcis-2707	66	21	a	a	DET
fcis-2707	66	22	mean	mean	NOUN
fcis-2707	66	23	of	of	ADP
fcis-2707	66	24	0	0	NUM
fcis-2707	66	25	and	and	CCONJ
fcis-2707	66	26	a	a	DET
fcis-2707	66	27	standard	standard	ADJ
fcis-2707	66	28	deviation	deviation	NOUN
fcis-2707	66	29	of	of	ADP
fcis-2707	66	30	0.01	0.01	NUM
fcis-2707	66	31	.	.	PUNCT
fcis-2707	67	1	for	for	ADP
fcis-2707	67	2	training	training	NOUN
fcis-2707	67	3	details	detail	NOUN
fcis-2707	67	4	,	,	PUNCT
fcis-2707	67	5	we	we	PRON
fcis-2707	67	6	choose	choose	VERB
fcis-2707	67	7	the	the	DET
fcis-2707	67	8	adam	adam	PROPN
fcis-2707	67	9	optimizer	optimizer	NOUN
fcis-2707	67	10	to	to	PART
fcis-2707	67	11	retrain	retrain	VERB
fcis-2707	67	12	the	the	DET
fcis-2707	67	13	model	model	NOUN
fcis-2707	67	14	,	,	PUNCT
fcis-2707	67	15	with	with	ADP
fcis-2707	67	16	an	an	DET
fcis-2707	67	17	initial	initial	ADJ
fcis-2707	67	18	learning	learning	NOUN
fcis-2707	67	19	rate	rate	NOUN
fcis-2707	67	20	of	of	ADP
fcis-2707	67	21	1e-4	1e-4	NUM
fcis-2707	67	22	,	,	PUNCT
fcis-2707	67	23	halved	halve	VERB
fcis-2707	67	24	every	every	DET
fcis-2707	67	25	100	100	NUM
fcis-2707	67	26	rounds	round	NOUN
fcis-2707	67	27	.	.	PUNCT
fcis-2707	68	1	there	there	PRON
fcis-2707	68	2	are	be	VERB
fcis-2707	68	3	two	two	NUM
fcis-2707	68	4	mainstream	mainstream	ADJ
fcis-2707	68	5	metrics	metric	NOUN
fcis-2707	68	6	for	for	ADP
fcis-2707	68	7	evaluating	evaluate	VERB
fcis-2707	68	8	the	the	DET
fcis-2707	68	9	performance	performance	NOUN
fcis-2707	68	10	in	in	ADP
fcis-2707	68	11	crowd	crowd	NOUN
fcis-2707	68	12	counting	counting	NOUN
fcis-2707	68	13	task	task	NOUN
fcis-2707	68	14	:	:	PUNCT
fcis-2707	68	15	mean	mean	ADJ
fcis-2707	68	16	absolute	absolute	ADJ
fcis-2707	68	17	error	error	NOUN
fcis-2707	68	18	(	(	PUNCT
fcis-2707	68	19	mae	mae	PROPN
fcis-2707	68	20	)	)	PUNCT
fcis-2707	68	21	and	and	CCONJ
fcis-2707	68	22	mean	mean	VERB
fcis-2707	68	23	squared	square	VERB
fcis-2707	68	24	error	error	NOUN
fcis-2707	68	25	(	(	PUNCT
fcis-2707	68	26	mse	mse	NOUN
fcis-2707	68	27	)	)	PUNCT
fcis-2707	68	28	.	.	PUNCT
fcis-2707	69	1	they	they	PRON
fcis-2707	69	2	are	be	AUX
fcis-2707	69	3	defined	define	VERB
fcis-2707	69	4	as	as	SCONJ
fcis-2707	69	5	follows	follow	VERB
fcis-2707	69	6	.	.	PUNCT
fcis-2707	70	1	1	1	NUM
fcis-2707	70	2	1	1	NUM
fcis-2707	70	3	n	n	NOUN
fcis-2707	70	4	i	i	PRON
fcis-2707	71	1	i	i	PRON
fcis-2707	72	1	i	i	PRON
fcis-2707	72	2	mae	mae	PROPN
fcis-2707	73	1	p	p	NOUN
fcis-2707	73	2	g	g	PROPN
fcis-2707	73	3	n	n	NOUN
fcis-2707	73	4	=	=	SYM
fcis-2707	73	5	=	=	SYM
fcis-2707	73	6	−	−	NOUN
fcis-2707	73	7	(	(	PUNCT
fcis-2707	73	8	3	3	NUM
fcis-2707	73	9	)	)	SYM
fcis-2707	73	10	21	21	NUM
fcis-2707	73	11	1	1	NUM
fcis-2707	73	12	n	n	NOUN
fcis-2707	73	13	i	i	PRON
fcis-2707	73	14	in	in	ADP
fcis-2707	73	15	i	i	PROPN
fcis-2707	73	16	mse	mse	VERB
fcis-2707	74	1	p	p	NOUN
fcis-2707	74	2	g	g	PROPN
fcis-2707	74	3	=	=	SYM
fcis-2707	74	4	=	=	SYM
fcis-2707	74	5	−	−	NOUN
fcis-2707	74	6	(	(	PUNCT
fcis-2707	74	7	4	4	NUM
fcis-2707	74	8	)	)	PUNCT
fcis-2707	74	9	3.2	3.2	NUM
fcis-2707	74	10	.	.	PUNCT
fcis-2707	74	11	comparison	comparison	NOUN
fcis-2707	74	12	experiment	experiment	NOUN
fcis-2707	74	13	we	we	PRON
fcis-2707	74	14	demonstrate	demonstrate	VERB
fcis-2707	74	15	the	the	DET
fcis-2707	74	16	effectiveness	effectiveness	NOUN
fcis-2707	74	17	of	of	ADP
fcis-2707	74	18	the	the	DET
fcis-2707	74	19	proposed	propose	VERB
fcis-2707	74	20	method	method	NOUN
fcis-2707	74	21	on	on	ADP
fcis-2707	74	22	four	four	NUM
fcis-2707	74	23	official	official	ADJ
fcis-2707	74	24	datasets	dataset	NOUN
fcis-2707	74	25	,	,	PUNCT
fcis-2707	74	26	and	and	CCONJ
fcis-2707	74	27	the	the	DET
fcis-2707	74	28	experimental	experimental	ADJ
fcis-2707	74	29	results	result	NOUN
fcis-2707	74	30	are	be	AUX
fcis-2707	74	31	shown	show	VERB
fcis-2707	74	32	in	in	ADP
fcis-2707	74	33	table	table	NOUN
fcis-2707	74	34	1	1	NUM
fcis-2707	74	35	(	(	PUNCT
fcis-2707	74	36	the	the	DET
fcis-2707	74	37	best	good	ADJ
fcis-2707	74	38	performance	performance	NOUN
fcis-2707	74	39	is	be	AUX
fcis-2707	74	40	indicted	indict	VERB
fcis-2707	74	41	by	by	ADP
fcis-2707	74	42	bold	bold	ADJ
fcis-2707	74	43	and	and	CCONJ
fcis-2707	74	44	the	the	DET
fcis-2707	74	45	second	second	ADJ
fcis-2707	74	46	best	good	ADJ
fcis-2707	74	47	is	be	AUX
fcis-2707	74	48	underlined	underline	VERB
fcis-2707	74	49	)	)	PUNCT
fcis-2707	74	50	.	.	PUNCT
fcis-2707	75	1	in	in	ADP
fcis-2707	75	2	the	the	DET
fcis-2707	75	3	shanghaitech	shanghaitech	NOUN
fcis-2707	75	4	part_a	part_a	VERB
fcis-2707	75	5	dataset	dataset	NOUN
fcis-2707	75	6	,	,	PUNCT
fcis-2707	75	7	our	our	PRON
fcis-2707	75	8	mae	mae	PROPN
fcis-2707	75	9	is	be	AUX
fcis-2707	75	10	0.33	0.33	NUM
fcis-2707	75	11	%	%	NOUN
fcis-2707	75	12	ahead	ahead	ADV
fcis-2707	75	13	of	of	ADP
fcis-2707	75	14	hanet	hanet	NOUN
fcis-2707	75	15	;	;	PUNCT
fcis-2707	75	16	for	for	ADP
fcis-2707	75	17	the	the	DET
fcis-2707	75	18	ucf_cc_50	ucf_cc_50	PROPN
fcis-2707	75	19	dataset	dataset	NOUN
fcis-2707	75	20	,	,	PUNCT
fcis-2707	75	21	it	it	PRON
fcis-2707	75	22	outperforms	outperform	VERB
fcis-2707	75	23	the	the	DET
fcis-2707	75	24	asnet	asnet	NOUN
fcis-2707	75	25	result	result	NOUN
fcis-2707	75	26	by	by	ADP
fcis-2707	75	27	4.5	4.5	NUM
fcis-2707	75	28	%	%	NOUN
fcis-2707	75	29	,	,	PUNCT
fcis-2707	75	30	while	while	SCONJ
fcis-2707	75	31	the	the	DET
fcis-2707	75	32	mse	mse	NOUN
fcis-2707	75	33	is	be	AUX
fcis-2707	75	34	2.59	2.59	NUM
fcis-2707	75	35	%	%	NOUN
fcis-2707	75	36	ahead	ahead	ADV
fcis-2707	75	37	.	.	PUNCT
fcis-2707	76	1	also	also	ADV
fcis-2707	76	2	,	,	PUNCT
fcis-2707	76	3	in	in	ADP
fcis-2707	76	4	the	the	DET
fcis-2707	76	5	ucfqnrf	ucfqnrf	NOUN
fcis-2707	76	6	dataset	dataset	NOUN
fcis-2707	76	7	,	,	PUNCT
fcis-2707	76	8	we	we	PRON
fcis-2707	76	9	improve	improve	VERB
fcis-2707	76	10	the	the	DET
fcis-2707	76	11	mse	mse	PROPN
fcis-2707	76	12	metric	metric	NOUN
fcis-2707	76	13	by	by	ADP
fcis-2707	76	14	1.03	1.03	NUM
fcis-2707	76	15	%	%	NOUN
fcis-2707	76	16	.	.	PUNCT
fcis-2707	77	1	to	to	PART
fcis-2707	77	2	visually	visually	ADV
fcis-2707	77	3	compare	compare	VERB
fcis-2707	77	4	the	the	DET
fcis-2707	77	5	effectiveness	effectiveness	NOUN
fcis-2707	77	6	of	of	ADP
fcis-2707	77	7	the	the	DET
fcis-2707	77	8	proposed	propose	VERB
fcis-2707	77	9	method	method	NOUN
fcis-2707	77	10	with	with	ADP
fcis-2707	77	11	ranet	ranet	NOUN
fcis-2707	77	12	,	,	PUNCT
fcis-2707	77	13	we	we	PRON
fcis-2707	77	14	select	select	VERB
fcis-2707	77	15	the	the	DET
fcis-2707	77	16	representative	representative	ADJ
fcis-2707	77	17	samples	sample	NOUN
fcis-2707	77	18	from	from	ADP
fcis-2707	77	19	each	each	DET
fcis-2707	77	20	dataset	dataset	NOUN
fcis-2707	77	21	for	for	ADP
fcis-2707	77	22	counting	count	VERB
fcis-2707	77	23	tests	test	NOUN
fcis-2707	77	24	,	,	PUNCT
fcis-2707	77	25	as	as	SCONJ
fcis-2707	77	26	shown	show	VERB
fcis-2707	77	27	in	in	ADP
fcis-2707	77	28	figure	figure	NOUN
fcis-2707	77	29	2	2	NUM
fcis-2707	77	30	.	.	PUNCT
fcis-2707	77	31	further	far	ADV
fcis-2707	77	32	,	,	PUNCT
fcis-2707	77	33	to	to	PART
fcis-2707	77	34	observe	observe	VERB
fcis-2707	77	35	the	the	DET
fcis-2707	77	36	overall	overall	ADJ
fcis-2707	77	37	prediction	prediction	NOUN
fcis-2707	77	38	effect	effect	NOUN
fcis-2707	77	39	of	of	ADP
fcis-2707	77	40	the	the	DET
fcis-2707	77	41	two	two	NUM
fcis-2707	77	42	on	on	ADP
fcis-2707	77	43	shanghaitech	shanghaitech	NOUN
fcis-2707	77	44	part_a	part_a	NOUN
fcis-2707	77	45	dataset	dataset	NOUN
fcis-2707	77	46	,	,	PUNCT
fcis-2707	77	47	we	we	PRON
fcis-2707	77	48	aggregate	aggregate	VERB
fcis-2707	77	49	the	the	DET
fcis-2707	77	50	pre	pre	NOUN
fcis-2707	77	51	-	-	ADJ
fcis-2707	77	52	gt	gt	ADJ
fcis-2707	77	53	information	information	NOUN
fcis-2707	77	54	for	for	ADP
fcis-2707	77	55	the	the	DET
fcis-2707	77	56	entire	entire	ADJ
fcis-2707	77	57	sample	sample	NOUN
fcis-2707	77	58	in	in	ADP
fcis-2707	77	59	this	this	DET
fcis-2707	77	60	dataset	dataset	NOUN
fcis-2707	77	61	and	and	CCONJ
fcis-2707	77	62	plot	plot	VERB
fcis-2707	77	63	it	it	PRON
fcis-2707	77	64	as	as	ADP
fcis-2707	77	65	a	a	DET
fcis-2707	77	66	scatter	scatter	NOUN
fcis-2707	77	67	diagram	diagram	NOUN
fcis-2707	77	68	with	with	ADP
fcis-2707	77	69	regression	regression	NOUN
fcis-2707	77	70	lines	line	NOUN
fcis-2707	77	71	,	,	PUNCT
fcis-2707	77	72	the	the	DET
fcis-2707	77	73	results	result	NOUN
fcis-2707	77	74	of	of	ADP
fcis-2707	77	75	which	which	PRON
fcis-2707	77	76	are	be	AUX
fcis-2707	77	77	shown	show	VERB
fcis-2707	77	78	in	in	ADP
fcis-2707	77	79	figure	figure	NOUN
fcis-2707	77	80	3	3	NUM
fcis-2707	77	81	,	,	PUNCT
fcis-2707	77	82	where	where	SCONJ
fcis-2707	77	83	the	the	DET
fcis-2707	77	84	red	red	ADJ
fcis-2707	77	85	auxiliary	auxiliary	ADJ
fcis-2707	77	86	line	line	NOUN
fcis-2707	77	87	y	y	PROPN
fcis-2707	77	88	=	=	PROPN
fcis-2707	77	89	x	x	NOUN
fcis-2707	77	90	indicates	indicate	VERB
fcis-2707	77	91	the	the	DET
fcis-2707	77	92	ideal	ideal	ADJ
fcis-2707	77	93	case	case	NOUN
fcis-2707	77	94	of	of	ADP
fcis-2707	77	95	100	100	NUM
fcis-2707	77	96	%	%	NOUN
fcis-2707	77	97	accuracy	accuracy	NOUN
fcis-2707	77	98	in	in	ADP
fcis-2707	77	99	counting	counting	NOUN
fcis-2707	77	100	.	.	PUNCT
fcis-2707	78	1	qualitatively	qualitatively	ADV
fcis-2707	78	2	,	,	PUNCT
fcis-2707	78	3	the	the	DET
fcis-2707	78	4	closeness	closeness	NOUN
fcis-2707	78	5	of	of	ADP
fcis-2707	78	6	the	the	DET
fcis-2707	78	7	blue	blue	ADJ
fcis-2707	78	8	regression	regression	NOUN
fcis-2707	78	9	line	line	NOUN
fcis-2707	78	10	to	to	ADP
fcis-2707	78	11	the	the	DET
fcis-2707	78	12	auxiliary	auxiliary	ADJ
fcis-2707	78	13	line	line	NOUN
fcis-2707	78	14	y	y	PROPN
fcis-2707	78	15	=	=	NOUN
fcis-2707	78	16	x	x	VERB
fcis-2707	78	17	is	be	AUX
fcis-2707	78	18	positively	positively	ADV
fcis-2707	78	19	correlated	correlate	VERB
fcis-2707	78	20	with	with	ADP
fcis-2707	78	21	the	the	DET
fcis-2707	78	22	quality	quality	NOUN
fcis-2707	78	23	of	of	ADP
fcis-2707	78	24	the	the	DET
fcis-2707	78	25	prediction	prediction	NOUN
fcis-2707	78	26	;	;	PUNCT
fcis-2707	78	27	quantitatively	quantitatively	ADV
fcis-2707	78	28	,	,	PUNCT
fcis-2707	78	29	the	the	PRON
fcis-2707	78	30	closer	close	ADV
fcis-2707	78	31	the	the	DET
fcis-2707	78	32	coefficient	coefficient	NOUN
fcis-2707	78	33	of	of	ADP
fcis-2707	78	34	determination	determination	NOUN
fcis-2707	78	35	2r	2r	NUM
fcis-2707	78	36	of	of	ADP
fcis-2707	78	37	the	the	DET
fcis-2707	78	38	regression	regression	NOUN
fcis-2707	78	39	line	line	NOUN
fcis-2707	78	40	is	be	AUX
fcis-2707	78	41	to	to	ADP
fcis-2707	78	42	1	1	NUM
fcis-2707	78	43	,	,	PUNCT
fcis-2707	78	44	the	the	PRON
fcis-2707	78	45	lower	low	ADJ
fcis-2707	78	46	the	the	DET
fcis-2707	78	47	overall	overall	ADJ
fcis-2707	78	48	error	error	NOUN
fcis-2707	78	49	fluctuation	fluctuation	NOUN
fcis-2707	78	50	is	be	AUX
fcis-2707	78	51	.	.	PUNCT
fcis-2707	79	1	37	37	NUM
fcis-2707	79	2	table	table	NOUN
fcis-2707	79	3	1	1	NUM
fcis-2707	79	4	.	.	PUNCT
fcis-2707	79	5	comparison	comparison	NOUN
fcis-2707	79	6	with	with	ADP
fcis-2707	79	7	different	different	ADJ
fcis-2707	79	8	methods	method	NOUN
fcis-2707	79	9	on	on	ADP
fcis-2707	79	10	four	four	NUM
fcis-2707	79	11	challenging	challenging	ADJ
fcis-2707	79	12	datasets	dataset	NOUN
fcis-2707	79	13	method	method	NOUN
fcis-2707	79	14	part_a	part_a	NOUN
fcis-2707	79	15	part_b	part_b	VERB
fcis-2707	79	16	ucf_cc_50	ucf_cc_50	PROPN
fcis-2707	79	17	ucf	ucf	PROPN
fcis-2707	79	18	-	-	PUNCT
fcis-2707	79	19	qnrf	qnrf	PROPN
fcis-2707	79	20	mae	mae	PROPN
fcis-2707	79	21	mse	mse	PROPN
fcis-2707	79	22	mae	mae	PROPN
fcis-2707	79	23	mse	mse	PROPN
fcis-2707	79	24	mae	mae	PROPN
fcis-2707	79	25	mse	mse	PROPN
fcis-2707	79	26	mae	mae	PROPN
fcis-2707	79	27	mse	mse	PROPN
fcis-2707	79	28	bl[12	bl[12	PROPN
fcis-2707	79	29	]	]	X
fcis-2707	79	30	62.8	62.8	NUM
fcis-2707	79	31	101.8	101.8	NUM
fcis-2707	79	32	7.7	7.7	NUM
fcis-2707	79	33	12.7	12.7	NUM
fcis-2707	79	34	229.3	229.3	NUM
fcis-2707	79	35	308.2	308.2	NUM
fcis-2707	79	36	88.7	88.7	NUM
fcis-2707	79	37	154.8	154.8	NUM
fcis-2707	79	38	ranet[7	ranet[7	NOUN
fcis-2707	79	39	]	]	X
fcis-2707	79	40	59.4	59.4	NUM
fcis-2707	79	41	102	102	NUM
fcis-2707	79	42	7.9	7.9	NUM
fcis-2707	79	43	12.9	12.9	NUM
fcis-2707	79	44	239.8	239.8	NUM
fcis-2707	79	45	319.4	319.4	NUM
fcis-2707	79	46	111	111	NUM
fcis-2707	79	47	190	190	NUM
fcis-2707	79	48	asnet[5	asnet[5	NOUN
fcis-2707	79	49	]	]	PUNCT
fcis-2707	79	50	57.78	57.78	NUM
fcis-2707	79	51	90.13	90.13	NUM
fcis-2707	80	1	174.84	174.84	NUM
fcis-2707	80	2	251.63	251.63	NUM
fcis-2707	80	3	91.59	91.59	NUM
fcis-2707	80	4	159.71	159.71	NUM
fcis-2707	80	5	libranet[13	libranet[13	X
fcis-2707	80	6	]	]	X
fcis-2707	80	7	55.9	55.9	NUM
fcis-2707	80	8	97.1	97.1	NUM
fcis-2707	80	9	7.3	7.3	NUM
fcis-2707	80	10	11.3	11.3	NUM
fcis-2707	80	11	181.2	181.2	NUM
fcis-2707	80	12	262.2	262.2	NUM
fcis-2707	80	13	88.1	88.1	NUM
fcis-2707	80	14	143.7	143.7	NUM
fcis-2707	80	15	amsnet[14	amsnet[14	PROPN
fcis-2707	80	16	]	]	X
fcis-2707	80	17	56.7	56.7	NUM
fcis-2707	80	18	93.4	93.4	NUM
fcis-2707	80	19	6.7	6.7	NUM
fcis-2707	80	20	10.2	10.2	NUM
fcis-2707	80	21	208.4	208.4	NUM
fcis-2707	80	22	297.3	297.3	NUM
fcis-2707	80	23	101.8	101.8	NUM
fcis-2707	80	24	163.2	163.2	NUM
fcis-2707	80	25	uot[15	uot[15	PROPN
fcis-2707	80	26	]	]	X
fcis-2707	80	27	58.1	58.1	NUM
fcis-2707	80	28	95.9	95.9	NUM
fcis-2707	80	29	6.5	6.5	NUM
fcis-2707	80	30	10.2	10.2	NUM
fcis-2707	80	31	83.3	83.3	NUM
fcis-2707	80	32	142.3	142.3	NUM
fcis-2707	80	33	urc[16	urc[16	NOUN
fcis-2707	80	34	]	]	PUNCT
fcis-2707	80	35	68.2	68.2	NUM
fcis-2707	80	36	115	115	NUM
fcis-2707	80	37	10.6	10.6	NUM
fcis-2707	80	38	16	16	NUM
fcis-2707	80	39	293.99	293.99	NUM
fcis-2707	80	40	443.09	443.09	NUM
fcis-2707	80	41	128.13	128.13	NUM
fcis-2707	80	42	218.05	218.05	NUM
fcis-2707	80	43	dkpnet[17	dkpnet[17	PROPN
fcis-2707	80	44	]	]	X
fcis-2707	80	45	55.6	55.6	NUM
fcis-2707	80	46	91	91	NUM
fcis-2707	80	47	6.6	6.6	NUM
fcis-2707	80	48	10.9	10.9	NUM
fcis-2707	80	49	81.4	81.4	NUM
fcis-2707	80	50	147.2	147.2	NUM
fcis-2707	80	51	hanet[6	hanet[6	NOUN
fcis-2707	80	52	]	]	PUNCT
fcis-2707	80	53	54.9	54.9	NUM
fcis-2707	80	54	91.2	91.2	NUM
fcis-2707	80	55	6.8	6.8	NUM
fcis-2707	80	56	11.5	11.5	NUM
fcis-2707	80	57	195.2	195.2	NUM
fcis-2707	80	58	268.6	268.6	NUM
fcis-2707	80	59	98	98	NUM
fcis-2707	80	60	179	179	NUM
fcis-2707	80	61	d2c[18	d2c[18	PROPN
fcis-2707	80	62	]	]	PUNCT
fcis-2707	80	63	59.6	59.6	NUM
fcis-2707	80	64	100.7	100.7	NUM
fcis-2707	80	65	6.7	6.7	NUM
fcis-2707	80	66	10.7	10.7	NUM
fcis-2707	80	67	221.5	221.5	NUM
fcis-2707	80	68	300.7	300.7	NUM
fcis-2707	80	69	84.8	84.8	NUM
fcis-2707	80	70	145.6	145.6	NUM
fcis-2707	80	71	ours	our	NOUN
fcis-2707	80	72	54.72	54.72	NUM
fcis-2707	80	73	93.76	93.76	NUM
fcis-2707	80	74	7.12	7.12	NUM
fcis-2707	80	75	12.86	12.86	NUM
fcis-2707	80	76	166.97	166.97	NUM
fcis-2707	80	77	245.12	245.12	NUM
fcis-2707	80	78	83.02	83.02	NUM
fcis-2707	80	79	140.84	140.84	NUM
fcis-2707	80	80	input	input	NOUN
fcis-2707	80	81	ranet	ranet	NOUN
fcis-2707	80	82	gt	gt	PROPN
fcis-2707	80	83	sh	sh	PROPN
fcis-2707	80	84	an	an	DET
fcis-2707	80	85	gh	gh	PROPN
fcis-2707	81	1	a	a	DET
fcis-2707	81	2	it	it	PRON
fcis-2707	81	3	e	e	NOUN
fcis-2707	81	4	ch	ch	NOUN
fcis-2707	81	5	a	a	PROPN
fcis-2707	81	6	sh	sh	PROPN
fcis-2707	81	7	an	an	DET
fcis-2707	81	8	gh	gh	PROPN
fcis-2707	81	9	a	a	DET
fcis-2707	81	10	it	it	PRON
fcis-2707	81	11	e	e	PROPN
fcis-2707	81	12	ch	ch	PROPN
fcis-2707	81	13	b	b	PROPN
fcis-2707	81	14	u	u	NOUN
fcis-2707	81	15	c	c	NOUN
fcis-2707	81	16	f	f	NOUN
fcis-2707	81	17	_	_	PUNCT
fcis-2707	81	18	c	c	NOUN
fcis-2707	82	1	c	c	NOUN
fcis-2707	82	2	_	_	NOUN
fcis-2707	82	3	5	5	NUM
fcis-2707	82	4	0	0	NUM
fcis-2707	82	5	u	u	NOUN
fcis-2707	82	6	c	c	PROPN
fcis-2707	82	7	fq	fq	NOUN
fcis-2707	82	8	n	n	ADP
fcis-2707	82	9	r	r	NOUN
fcis-2707	82	10	f	f	PROPN
fcis-2707	82	11	count:1309.83	count:1309.83	PROPN
fcis-2707	82	12	count:1229.57	count:1229.57	PROPN
fcis-2707	82	13	count:1213	count:1213	NOUN
fcis-2707	82	14	count:122.35	count:122.35	PROPN
fcis-2707	82	15	count:116.02	count:116.02	PROPN
fcis-2707	82	16	count:115	count:115	PROPN
fcis-2707	82	17	ours	ours	PRON
fcis-2707	82	18	figure	figure	NOUN
fcis-2707	82	19	2	2	NUM
fcis-2707	82	20	.	.	PUNCT
fcis-2707	82	21	visual	visual	ADJ
fcis-2707	82	22	comparison	comparison	NOUN
fcis-2707	82	23	of	of	ADP
fcis-2707	82	24	different	different	ADJ
fcis-2707	82	25	methods	method	NOUN
fcis-2707	82	26	figure	figure	VERB
fcis-2707	82	27	3	3	NUM
fcis-2707	82	28	.	.	PUNCT
fcis-2707	82	29	scatter	scatter	NOUN
fcis-2707	82	30	plot	plot	NOUN
fcis-2707	82	31	vs.	vs.	ADP
fcis-2707	82	32	regression	regression	NOUN
fcis-2707	82	33	line	line	NOUN
fcis-2707	82	34	for	for	ADP
fcis-2707	82	35	different	different	ADJ
fcis-2707	82	36	methods	method	NOUN
fcis-2707	82	37	4	4	NUM
fcis-2707	82	38	.	.	PUNCT
fcis-2707	82	39	conclusion	conclusion	NOUN
fcis-2707	82	40	in	in	ADP
fcis-2707	82	41	this	this	DET
fcis-2707	82	42	paper	paper	NOUN
fcis-2707	82	43	,	,	PUNCT
fcis-2707	82	44	we	we	PRON
fcis-2707	82	45	dissect	dissect	VERB
fcis-2707	82	46	the	the	DET
fcis-2707	82	47	current	current	ADJ
fcis-2707	82	48	problems	problem	NOUN
fcis-2707	82	49	faced	face	VERB
fcis-2707	82	50	by	by	ADP
fcis-2707	82	51	dense	dense	ADJ
fcis-2707	82	52	crowd	crowd	NOUN
fcis-2707	82	53	counting	counting	NOUN
fcis-2707	82	54	,	,	PUNCT
fcis-2707	82	55	including	include	VERB
fcis-2707	82	56	noisy	noisy	ADJ
fcis-2707	82	57	background	background	NOUN
fcis-2707	82	58	,	,	PUNCT
fcis-2707	82	59	mutual	mutual	ADJ
fcis-2707	82	60	occlusion	occlusion	NOUN
fcis-2707	82	61	and	and	CCONJ
fcis-2707	82	62	variable	variable	ADJ
fcis-2707	82	63	scale	scale	NOUN
fcis-2707	82	64	.	.	PUNCT
fcis-2707	83	1	a	a	DET
fcis-2707	83	2	dual	dual	ADJ
fcis-2707	83	3	-	-	PUNCT
fcis-2707	83	4	track	track	NOUN
fcis-2707	83	5	network	network	NOUN
fcis-2707	83	6	is	be	AUX
fcis-2707	83	7	designed	design	VERB
fcis-2707	83	8	,	,	PUNCT
fcis-2707	83	9	using	use	VERB
fcis-2707	83	10	heterogeneous	heterogeneous	ADJ
fcis-2707	83	11	pyramid	pyramid	NOUN
fcis-2707	83	12	modules	module	NOUN
fcis-2707	83	13	to	to	PART
fcis-2707	83	14	obtain	obtain	VERB
fcis-2707	83	15	global	global	ADJ
fcis-2707	83	16	and	and	CCONJ
fcis-2707	83	17	local	local	ADJ
fcis-2707	83	18	features	feature	NOUN
fcis-2707	83	19	respectively	respectively	ADV
fcis-2707	83	20	,	,	PUNCT
fcis-2707	83	21	which	which	PRON
fcis-2707	83	22	are	be	AUX
fcis-2707	83	23	transformed	transform	VERB
fcis-2707	83	24	into	into	ADP
fcis-2707	83	25	hybrid	hybrid	ADJ
fcis-2707	83	26	attention	attention	NOUN
fcis-2707	83	27	based	base	VERB
fcis-2707	83	28	on	on	ADP
fcis-2707	83	29	the	the	DET
fcis-2707	83	30	softmax	softmax	NOUN
fcis-2707	83	31	algorithm	algorithm	NOUN
fcis-2707	83	32	and	and	CCONJ
fcis-2707	83	33	fused	fuse	VERB
fcis-2707	83	34	with	with	ADP
fcis-2707	83	35	highresolution	highresolution	NOUN
fcis-2707	83	36	feature	feature	NOUN
fcis-2707	83	37	maps	map	NOUN
fcis-2707	83	38	to	to	PART
fcis-2707	83	39	effectively	effectively	ADV
fcis-2707	83	40	deal	deal	VERB
fcis-2707	83	41	with	with	ADP
fcis-2707	83	42	the	the	DET
fcis-2707	83	43	problem	problem	NOUN
fcis-2707	83	44	of	of	ADP
fcis-2707	83	45	responsible	responsible	ADJ
fcis-2707	83	46	target	target	NOUN
fcis-2707	83	47	overlap	overlap	NOUN
fcis-2707	83	48	and	and	CCONJ
fcis-2707	83	49	background	background	NOUN
fcis-2707	83	50	confusion	confusion	NOUN
fcis-2707	83	51	,	,	PUNCT
fcis-2707	83	52	on	on	ADP
fcis-2707	83	53	the	the	DET
fcis-2707	83	54	other	other	ADJ
fcis-2707	83	55	hand	hand	NOUN
fcis-2707	83	56	,	,	PUNCT
fcis-2707	83	57	the	the	DET
fcis-2707	83	58	pyramid	pyramid	NOUN
fcis-2707	83	59	paradigm	paradigm	NOUN
fcis-2707	83	60	itself	itself	PRON
fcis-2707	83	61	has	have	VERB
fcis-2707	83	62	strong	strong	ADJ
fcis-2707	83	63	learning	learning	NOUN
fcis-2707	83	64	capability	capability	NOUN
fcis-2707	83	65	for	for	ADP
fcis-2707	83	66	variable	variable	ADJ
fcis-2707	83	67	scales	scale	NOUN
fcis-2707	83	68	.	.	PUNCT
fcis-2707	84	1	experiments	experiment	NOUN
fcis-2707	84	2	show	show	VERB
fcis-2707	84	3	that	that	SCONJ
fcis-2707	84	4	this	this	DET
fcis-2707	84	5	strategy	strategy	NOUN
fcis-2707	84	6	is	be	AUX
fcis-2707	84	7	effective	effective	ADJ
fcis-2707	84	8	and	and	CCONJ
fcis-2707	84	9	has	have	VERB
fcis-2707	84	10	more	more	ADV
fcis-2707	84	11	stable	stable	ADJ
fcis-2707	84	12	performance	performance	NOUN
fcis-2707	84	13	.	.	PUNCT
fcis-2707	85	1	38	38	NUM
fcis-2707	85	2	references	reference	NOUN
fcis-2707	85	3	[	[	X
fcis-2707	85	4	1	1	NUM
fcis-2707	85	5	]	]	X
fcis-2707	85	6	zhang	zhang	PROPN
fcis-2707	85	7	y	y	PROPN
fcis-2707	85	8	,	,	PUNCT
fcis-2707	85	9	zhou	zhou	PROPN
fcis-2707	85	10	d	d	PROPN
fcis-2707	85	11	,	,	PUNCT
fcis-2707	85	12	chen	chen	PROPN
fcis-2707	85	13	s	s	PROPN
fcis-2707	85	14	,	,	PUNCT
fcis-2707	85	15	et	et	PROPN
fcis-2707	85	16	al	al	PROPN
fcis-2707	85	17	.	.	PUNCT
fcis-2707	85	18	single	single	ADJ
fcis-2707	85	19	-	-	PUNCT
fcis-2707	85	20	image	image	NOUN
fcis-2707	85	21	crowd	crowd	NOUN
fcis-2707	85	22	counting	counting	NOUN
fcis-2707	85	23	via	via	ADP
fcis-2707	85	24	multi	multi	ADJ
fcis-2707	85	25	-	-	ADJ
fcis-2707	85	26	column	column	ADJ
fcis-2707	85	27	convolutional	convolutional	ADJ
fcis-2707	85	28	neural	neural	ADJ
fcis-2707	85	29	network[c	network[c	PROPN
fcis-2707	85	30	]	]	X
fcis-2707	85	31	//proceedings	//proceeding	NOUN
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fcis-2707	85	33	the	the	DET
fcis-2707	85	34	ieee	ieee	NOUN
fcis-2707	85	35	conference	conference	NOUN
fcis-2707	85	36	on	on	ADP
fcis-2707	85	37	computer	computer	NOUN
fcis-2707	85	38	vision	vision	NOUN
fcis-2707	85	39	and	and	CCONJ
fcis-2707	85	40	pattern	pattern	NOUN
fcis-2707	85	41	recognition	recognition	NOUN
fcis-2707	85	42	.	.	PUNCT
fcis-2707	86	1	2016	2016	NUM
fcis-2707	86	2	:	:	PUNCT
fcis-2707	86	3	589	589	NUM
fcis-2707	86	4	-	-	SYM
fcis-2707	86	5	597	597	NUM
fcis-2707	86	6	.	.	PUNCT
fcis-2707	87	1	[	[	X
fcis-2707	87	2	2	2	X
fcis-2707	87	3	]	]	PUNCT
fcis-2707	87	4	babu	babu	PROPN
fcis-2707	87	5	sam	sam	PROPN
fcis-2707	87	6	d	d	PROPN
fcis-2707	87	7	,	,	PUNCT
fcis-2707	87	8	surya	surya	PROPN
fcis-2707	87	9	s	s	PROPN
fcis-2707	87	10	,	,	PUNCT
fcis-2707	87	11	venkatesh	venkatesh	PROPN
fcis-2707	87	12	babu	babu	PROPN
fcis-2707	87	13	r.	r.	PROPN
fcis-2707	87	14	switching	switch	VERB
fcis-2707	87	15	convolutional	convolutional	ADJ
fcis-2707	87	16	neural	neural	ADJ
fcis-2707	87	17	network	network	NOUN
fcis-2707	87	18	for	for	ADP
fcis-2707	87	19	crowd	crowd	NOUN
fcis-2707	87	20	counting[c]//	counting[c]//	PROPN
fcis-2707	87	21	proceedings	proceeding	NOUN
fcis-2707	87	22	of	of	ADP
fcis-2707	87	23	the	the	DET
fcis-2707	87	24	ieee	ieee	NOUN
fcis-2707	87	25	conference	conference	NOUN
fcis-2707	87	26	on	on	ADP
fcis-2707	87	27	computer	computer	NOUN
fcis-2707	87	28	vision	vision	NOUN
fcis-2707	87	29	and	and	CCONJ
fcis-2707	87	30	pattern	pattern	NOUN
fcis-2707	87	31	recognition	recognition	NOUN
fcis-2707	87	32	.	.	PUNCT
fcis-2707	88	1	2017	2017	NUM
fcis-2707	88	2	:	:	PUNCT
fcis-2707	88	3	5744	5744	NUM
fcis-2707	88	4	-	-	SYM
fcis-2707	88	5	5752	5752	NUM
fcis-2707	88	6	.	.	PUNCT
fcis-2707	89	1	[	[	X
fcis-2707	89	2	3	3	X
fcis-2707	89	3	]	]	X
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fcis-2707	89	6	,	,	PUNCT
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fcis-2707	89	9	,	,	PUNCT
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fcis-2707	89	13	:	:	PUNCT
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fcis-2707	89	16	neural	neural	ADJ
fcis-2707	89	17	networks	network	NOUN
fcis-2707	89	18	for	for	ADP
fcis-2707	89	19	understanding	understand	VERB
fcis-2707	89	20	the	the	DET
fcis-2707	89	21	highly	highly	ADV
fcis-2707	89	22	congested	congested	ADJ
fcis-2707	89	23	scenes[c]//proceedings	scenes[c]//proceeding	NOUN
fcis-2707	89	24	of	of	ADP
fcis-2707	89	25	the	the	DET
fcis-2707	89	26	ieee	ieee	NOUN
fcis-2707	89	27	conference	conference	NOUN
fcis-2707	89	28	on	on	ADP
fcis-2707	89	29	computer	computer	NOUN
fcis-2707	89	30	vision	vision	NOUN
fcis-2707	89	31	and	and	CCONJ
fcis-2707	89	32	pattern	pattern	NOUN
fcis-2707	89	33	recognition	recognition	NOUN
fcis-2707	89	34	.	.	PUNCT
fcis-2707	90	1	2018	2018	NUM
fcis-2707	90	2	:	:	PUNCT
fcis-2707	90	3	1091	1091	NUM
fcis-2707	90	4	-	-	SYM
fcis-2707	90	5	1100	1100	NUM
fcis-2707	90	6	.	.	PUNCT
fcis-2707	91	1	[	[	X
fcis-2707	91	2	4	4	X
fcis-2707	91	3	]	]	X
fcis-2707	91	4	cao	cao	PROPN
fcis-2707	91	5	x	x	PROPN
fcis-2707	91	6	,	,	PUNCT
fcis-2707	91	7	wang	wang	PROPN
fcis-2707	91	8	z	z	PROPN
fcis-2707	91	9	,	,	PUNCT
fcis-2707	91	10	zhao	zhao	PROPN
fcis-2707	91	11	y	y	PROPN
fcis-2707	91	12	,	,	PUNCT
fcis-2707	91	13	et	et	PROPN
fcis-2707	91	14	al	al	PROPN
fcis-2707	91	15	.	.	PROPN
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fcis-2707	91	17	aggregation	aggregation	NOUN
fcis-2707	91	18	network	network	NOUN
fcis-2707	91	19	for	for	ADP
fcis-2707	91	20	accurate	accurate	ADJ
fcis-2707	91	21	and	and	CCONJ
fcis-2707	91	22	efficient	efficient	ADJ
fcis-2707	91	23	crowd	crowd	NOUN
fcis-2707	91	24	counting[c]//proceedings	counting[c]//proceeding	NOUN
fcis-2707	91	25	of	of	ADP
fcis-2707	91	26	the	the	DET
fcis-2707	91	27	european	european	PROPN
fcis-2707	91	28	conference	conference	PROPN
fcis-2707	91	29	on	on	ADP
fcis-2707	91	30	computer	computer	NOUN
fcis-2707	91	31	vision	vision	NOUN
fcis-2707	91	32	(	(	PUNCT
fcis-2707	91	33	eccv	eccv	ADV
fcis-2707	91	34	)	)	PUNCT
fcis-2707	91	35	.	.	PUNCT
fcis-2707	92	1	2018	2018	NUM
fcis-2707	92	2	:	:	PUNCT
fcis-2707	92	3	734750	734750	NUM
fcis-2707	92	4	.	.	PUNCT
fcis-2707	93	1	[	[	X
fcis-2707	93	2	5	5	NUM
fcis-2707	93	3	]	]	X
fcis-2707	93	4	jiang	jiang	PROPN
fcis-2707	93	5	x	x	PROPN
fcis-2707	93	6	,	,	PUNCT
fcis-2707	93	7	zhang	zhang	PROPN
fcis-2707	93	8	l	l	PROPN
fcis-2707	93	9	,	,	PUNCT
fcis-2707	93	10	xu	xu	PROPN
fcis-2707	93	11	m	m	PROPN
fcis-2707	93	12	,	,	PUNCT
fcis-2707	93	13	et	et	PROPN
fcis-2707	93	14	al	al	PROPN
fcis-2707	93	15	.	.	PUNCT
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fcis-2707	93	17	scaling	scale	VERB
fcis-2707	93	18	for	for	ADP
fcis-2707	93	19	crowd	crowd	NOUN
fcis-2707	93	20	counting[c]//proceedings	counting[c]//proceeding	NOUN
fcis-2707	93	21	of	of	ADP
fcis-2707	93	22	the	the	DET
fcis-2707	93	23	ieee	ieee	NOUN
fcis-2707	93	24	/	/	SYM
fcis-2707	93	25	cvf	cvf	NOUN
fcis-2707	93	26	conference	conference	NOUN
fcis-2707	93	27	on	on	ADP
fcis-2707	93	28	computer	computer	NOUN
fcis-2707	93	29	vision	vision	NOUN
fcis-2707	93	30	and	and	CCONJ
fcis-2707	93	31	pattern	pattern	NOUN
fcis-2707	93	32	recognition	recognition	NOUN
fcis-2707	93	33	.	.	PUNCT
fcis-2707	94	1	2020	2020	NUM
fcis-2707	94	2	:	:	PUNCT
fcis-2707	94	3	4706	4706	NUM
fcis-2707	94	4	-	-	SYM
fcis-2707	94	5	4715	4715	NUM
fcis-2707	94	6	.	.	PUNCT
fcis-2707	95	1	[	[	X
fcis-2707	95	2	6	6	NUM
fcis-2707	95	3	]	]	PUNCT
fcis-2707	95	4	wang	wang	PROPN
fcis-2707	95	5	f	f	PROPN
fcis-2707	95	6	,	,	PUNCT
fcis-2707	95	7	sang	sing	VERB
fcis-2707	95	8	j	j	PROPN
fcis-2707	95	9	,	,	PUNCT
fcis-2707	95	10	wu	wu	PROPN
fcis-2707	95	11	z	z	PROPN
fcis-2707	95	12	,	,	PUNCT
fcis-2707	95	13	et	et	PROPN
fcis-2707	95	14	al	al	PROPN
fcis-2707	95	15	.	.	PUNCT
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fcis-2707	95	17	attention	attention	NOUN
fcis-2707	95	18	network	network	NOUN
fcis-2707	95	19	based	base	VERB
fcis-2707	95	20	on	on	ADP
fcis-2707	95	21	progressive	progressive	ADJ
fcis-2707	95	22	embedding	embed	VERB
fcis-2707	95	23	scale	scale	NOUN
fcis-2707	95	24	-	-	PUNCT
fcis-2707	95	25	context	context	NOUN
fcis-2707	95	26	for	for	ADP
fcis-2707	95	27	crowd	crowd	NOUN
fcis-2707	95	28	counting[j	counting[j	NOUN
fcis-2707	95	29	]	]	PUNCT
fcis-2707	95	30	.	.	PUNCT
fcis-2707	96	1	information	information	NOUN
fcis-2707	96	2	sciences	sciences	PROPN
fcis-2707	96	3	,	,	PUNCT
fcis-2707	96	4	2022	2022	NUM
fcis-2707	96	5	,	,	PUNCT
fcis-2707	96	6	591	591	NUM
fcis-2707	96	7	:	:	PUNCT
fcis-2707	96	8	306	306	NUM
fcis-2707	96	9	-	-	SYM
fcis-2707	96	10	318	318	NUM
fcis-2707	96	11	.	.	PUNCT
fcis-2707	97	1	[	[	X
fcis-2707	97	2	7	7	X
fcis-2707	97	3	]	]	X
fcis-2707	97	4	zhang	zhang	PROPN
fcis-2707	97	5	a	a	PROPN
fcis-2707	97	6	,	,	PUNCT
fcis-2707	97	7	shen	shen	PROPN
fcis-2707	97	8	j	j	PROPN
fcis-2707	97	9	,	,	PUNCT
fcis-2707	97	10	xiao	xiao	PROPN
fcis-2707	97	11	z	z	PROPN
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fcis-2707	97	13	et	et	PROPN
fcis-2707	97	14	al	al	PROPN
fcis-2707	97	15	.	.	PUNCT
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fcis-2707	97	18	network	network	NOUN
fcis-2707	97	19	for	for	ADP
fcis-2707	97	20	crowd	crowd	NOUN
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fcis-2707	97	23	the	the	DET
fcis-2707	97	24	ieee	ieee	NOUN
fcis-2707	97	25	/	/	SYM
fcis-2707	97	26	cvf	cvf	NOUN
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fcis-2707	97	28	conference	conference	NOUN
fcis-2707	97	29	on	on	ADP
fcis-2707	97	30	computer	computer	NOUN
fcis-2707	97	31	vision	vision	NOUN
fcis-2707	97	32	.	.	PUNCT
fcis-2707	98	1	2019	2019	NUM
fcis-2707	98	2	:	:	PUNCT
fcis-2707	98	3	6788	6788	NUM
fcis-2707	98	4	-	-	SYM
fcis-2707	98	5	6797	6797	NUM
fcis-2707	98	6	.	.	PUNCT
fcis-2707	99	1	[	[	X
fcis-2707	99	2	8	8	NUM
fcis-2707	99	3	]	]	X
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fcis-2707	99	5	l	l	PROPN
fcis-2707	99	6	,	,	PUNCT
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fcis-2707	99	8	c.	c.	PROPN
fcis-2707	99	9	coarse	coarse	PROPN
fcis-2707	99	10	-	-	PUNCT
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fcis-2707	99	13	-	-	PUNCT
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fcis-2707	99	19	-	-	PUNCT
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fcis-2707	99	21	loss	loss	NOUN
fcis-2707	99	22	for	for	ADP
fcis-2707	99	23	crowd	crowd	NOUN
fcis-2707	99	24	density	density	NOUN
fcis-2707	99	25	map	map	NOUN
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fcis-2707	99	27	of	of	ADP
fcis-2707	99	28	the	the	DET
fcis-2707	99	29	ieee	ieee	NOUN
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fcis-2707	99	31	cvf	cvf	NOUN
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fcis-2707	99	34	on	on	ADP
fcis-2707	99	35	applications	application	NOUN
fcis-2707	99	36	of	of	ADP
fcis-2707	99	37	computer	computer	NOUN
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fcis-2707	99	39	.	.	PUNCT
fcis-2707	100	1	2021	2021	NUM
fcis-2707	100	2	:	:	PUNCT
fcis-2707	100	3	36753684	36753684	NUM
fcis-2707	100	4	.	.	PUNCT
fcis-2707	101	1	[	[	X
fcis-2707	101	2	9	9	NUM
fcis-2707	101	3	]	]	SYM
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fcis-2707	101	5	k	k	NOUN
fcis-2707	101	6	,	,	PUNCT
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fcis-2707	101	12	networks	network	NOUN
fcis-2707	101	13	for	for	ADP
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fcis-2707	101	15	-	-	PUNCT
fcis-2707	101	16	scale	scale	NOUN
fcis-2707	101	17	image	image	NOUN
fcis-2707	101	18	recognition[j	recognition[j	NOUN
fcis-2707	101	19	]	]	PUNCT
fcis-2707	101	20	.	.	PUNCT
fcis-2707	102	1	arxiv	arxiv	PROPN
fcis-2707	102	2	preprint	preprint	PROPN
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fcis-2707	102	4	,	,	PUNCT
fcis-2707	102	5	2014	2014	NUM
fcis-2707	102	6	.	.	PUNCT
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fcis-2707	103	2	10	10	NUM
fcis-2707	103	3	]	]	PUNCT
fcis-2707	103	4	idrees	idree	NOUN
fcis-2707	103	5	h	h	NOUN
fcis-2707	103	6	,	,	PUNCT
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fcis-2707	103	8	i	i	PRON
fcis-2707	103	9	,	,	PUNCT
fcis-2707	103	10	seibert	seibert	PROPN
fcis-2707	103	11	c	c	PROPN
fcis-2707	103	12	,	,	PUNCT
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fcis-2707	104	4	multi	multi	ADJ
fcis-2707	104	5	-	-	ADJ
fcis-2707	104	6	scale	scale	ADJ
fcis-2707	104	7	counting	counting	NOUN
fcis-2707	104	8	in	in	ADP
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fcis-2707	104	12	images[c]//proceedings	images[c]//proceeding	NOUN
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fcis-2707	104	14	the	the	DET
fcis-2707	104	15	ieee	ieee	NOUN
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fcis-2707	104	18	computer	computer	NOUN
fcis-2707	104	19	vision	vision	NOUN
fcis-2707	104	20	and	and	CCONJ
fcis-2707	104	21	pattern	pattern	NOUN
fcis-2707	104	22	recognition	recognition	NOUN
fcis-2707	104	23	.	.	PUNCT
fcis-2707	105	1	2013	2013	NUM
fcis-2707	105	2	:	:	PUNCT
fcis-2707	105	3	2547	2547	NUM
fcis-2707	105	4	-	-	SYM
fcis-2707	105	5	2554	2554	NUM
fcis-2707	105	6	.	.	PUNCT
fcis-2707	106	1	[	[	X
fcis-2707	106	2	11	11	NUM
fcis-2707	106	3	]	]	PUNCT
fcis-2707	106	4	idrees	idree	NOUN
fcis-2707	106	5	h	h	PROPN
fcis-2707	106	6	,	,	PUNCT
fcis-2707	106	7	tayyab	tayyab	PROPN
fcis-2707	106	8	m	m	PROPN
fcis-2707	106	9	,	,	PUNCT
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fcis-2707	106	13	et	et	PROPN
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fcis-2707	106	15	.	.	PUNCT
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fcis-2707	106	17	loss	loss	NOUN
fcis-2707	106	18	for	for	ADP
fcis-2707	106	19	counting	counting	NOUN
fcis-2707	106	20	,	,	PUNCT
fcis-2707	106	21	density	density	NOUN
fcis-2707	106	22	map	map	NOUN
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fcis-2707	106	24	and	and	CCONJ
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fcis-2707	106	26	in	in	ADP
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fcis-2707	106	28	crowds[c]//proceedings	crowds[c]//proceeding	NOUN
fcis-2707	106	29	of	of	ADP
fcis-2707	106	30	the	the	DET
fcis-2707	106	31	european	european	PROPN
fcis-2707	106	32	conference	conference	PROPN
fcis-2707	106	33	on	on	ADP
fcis-2707	106	34	computer	computer	NOUN
fcis-2707	106	35	vision	vision	NOUN
fcis-2707	106	36	(	(	PUNCT
fcis-2707	106	37	eccv	eccv	ADV
fcis-2707	106	38	)	)	PUNCT
fcis-2707	106	39	.	.	PUNCT
fcis-2707	107	1	2018	2018	NUM
fcis-2707	107	2	:	:	PUNCT
fcis-2707	107	3	532	532	NUM
fcis-2707	107	4	-	-	SYM
fcis-2707	107	5	546	546	NUM
fcis-2707	107	6	.	.	PUNCT
fcis-2707	108	1	[	[	X
fcis-2707	108	2	12	12	NUM
fcis-2707	108	3	]	]	X
fcis-2707	108	4	ma	ma	PROPN
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fcis-2707	108	6	,	,	PUNCT
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fcis-2707	108	9	,	,	PUNCT
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fcis-2707	108	11	x	x	NOUN
fcis-2707	108	12	,	,	PUNCT
fcis-2707	108	13	et	et	PROPN
fcis-2707	108	14	al	al	PROPN
fcis-2707	108	15	.	.	PUNCT
fcis-2707	109	1	bayesian	bayesian	NOUN
fcis-2707	109	2	loss	loss	NOUN
fcis-2707	109	3	for	for	ADP
fcis-2707	109	4	crowd	crowd	NOUN
fcis-2707	109	5	count	count	NOUN
fcis-2707	109	6	estimation	estimation	NOUN
fcis-2707	109	7	with	with	ADP
fcis-2707	109	8	point	point	NOUN
fcis-2707	109	9	supervision[c]//proceedings	supervision[c]//proceeding	NOUN
fcis-2707	109	10	of	of	ADP
fcis-2707	109	11	the	the	DET
fcis-2707	109	12	ieee	ieee	NOUN
fcis-2707	109	13	/	/	SYM
fcis-2707	109	14	cvf	cvf	NOUN
fcis-2707	109	15	international	international	ADJ
fcis-2707	109	16	conference	conference	NOUN
fcis-2707	109	17	on	on	ADP
fcis-2707	109	18	computer	computer	NOUN
fcis-2707	109	19	vision	vision	NOUN
fcis-2707	109	20	.	.	PUNCT
fcis-2707	110	1	2019	2019	NUM
fcis-2707	110	2	:	:	PUNCT
fcis-2707	110	3	6142	6142	NUM
fcis-2707	110	4	-	-	SYM
fcis-2707	110	5	6151	6151	NUM
fcis-2707	110	6	.	.	PUNCT
fcis-2707	111	1	[	[	X
fcis-2707	111	2	13	13	NUM
fcis-2707	111	3	]	]	X
fcis-2707	111	4	liu	liu	PROPN
fcis-2707	111	5	l	l	PROPN
fcis-2707	111	6	,	,	PUNCT
fcis-2707	111	7	lu	lu	PROPN
fcis-2707	111	8	h	h	NOUN
fcis-2707	111	9	,	,	PUNCT
fcis-2707	111	10	zou	zou	PROPN
fcis-2707	111	11	h	h	PROPN
fcis-2707	111	12	,	,	PUNCT
fcis-2707	111	13	et	et	PROPN
fcis-2707	111	14	al	al	PROPN
fcis-2707	111	15	.	.	PUNCT
fcis-2707	112	1	weighing	weigh	VERB
fcis-2707	112	2	counts	count	NOUN
fcis-2707	112	3	:	:	PUNCT
fcis-2707	112	4	sequential	sequential	ADJ
fcis-2707	112	5	crowd	crowd	NOUN
fcis-2707	112	6	counting	counting	NOUN
fcis-2707	112	7	by	by	ADP
fcis-2707	112	8	reinforcement	reinforcement	NOUN
fcis-2707	112	9	learning[c]//european	learning[c]//european	PROPN
fcis-2707	112	10	conference	conference	NOUN
fcis-2707	112	11	on	on	ADP
fcis-2707	112	12	computer	computer	NOUN
fcis-2707	112	13	vision	vision	NOUN
fcis-2707	112	14	.	.	PUNCT
fcis-2707	113	1	springer	springer	NOUN
fcis-2707	113	2	,	,	PUNCT
fcis-2707	113	3	cham	cham	PROPN
fcis-2707	113	4	,	,	PUNCT
fcis-2707	113	5	2020	2020	NUM
fcis-2707	113	6	:	:	PUNCT
fcis-2707	113	7	164	164	NUM
fcis-2707	113	8	-	-	SYM
fcis-2707	113	9	181	181	NUM
fcis-2707	113	10	.	.	PUNCT
fcis-2707	114	1	[	[	X
fcis-2707	114	2	14	14	NUM
fcis-2707	114	3	]	]	SYM
fcis-2707	114	4	hu	hu	PROPN
fcis-2707	115	1	y	y	PROPN
fcis-2707	115	2	,	,	PUNCT
fcis-2707	115	3	jiang	jiang	PROPN
fcis-2707	115	4	x	x	PROPN
fcis-2707	115	5	,	,	PUNCT
fcis-2707	115	6	liu	liu	PROPN
fcis-2707	115	7	x	x	PROPN
fcis-2707	115	8	,	,	PUNCT
fcis-2707	115	9	et	et	PROPN
fcis-2707	115	10	al	al	PROPN
fcis-2707	115	11	.	.	PUNCT
fcis-2707	116	1	nas	nas	PROPN
fcis-2707	116	2	-	-	PUNCT
fcis-2707	116	3	count	count	NOUN
fcis-2707	116	4	:	:	PUNCT
fcis-2707	116	5	counting	count	VERB
fcis-2707	116	6	-	-	PUNCT
fcis-2707	116	7	by	by	ADP
fcis-2707	116	8	-	-	PUNCT
fcis-2707	116	9	density	density	NOUN
fcis-2707	116	10	with	with	ADP
fcis-2707	116	11	neural	neural	ADJ
fcis-2707	116	12	architecture	architecture	NOUN
fcis-2707	116	13	search[c]//european	search[c]//european	PROPN
fcis-2707	116	14	conference	conference	NOUN
fcis-2707	116	15	on	on	ADP
fcis-2707	116	16	computer	computer	NOUN
fcis-2707	116	17	vision	vision	NOUN
fcis-2707	116	18	.	.	PUNCT
fcis-2707	117	1	springer	springer	NOUN
fcis-2707	117	2	,	,	PUNCT
fcis-2707	117	3	cham	cham	PROPN
fcis-2707	117	4	,	,	PUNCT
fcis-2707	117	5	2020	2020	NUM
fcis-2707	117	6	:	:	PUNCT
fcis-2707	118	1	747	747	NUM
fcis-2707	118	2	-	-	SYM
fcis-2707	118	3	766	766	NUM
fcis-2707	118	4	.	.	PUNCT
fcis-2707	119	1	[	[	X
fcis-2707	119	2	15	15	NUM
fcis-2707	119	3	]	]	X
fcis-2707	119	4	ma	ma	PROPN
fcis-2707	119	5	z	z	PROPN
fcis-2707	119	6	,	,	PUNCT
fcis-2707	119	7	wei	wei	PROPN
fcis-2707	119	8	x	x	PROPN
fcis-2707	119	9	,	,	PUNCT
fcis-2707	119	10	hong	hong	PROPN
fcis-2707	119	11	x	x	NOUN
fcis-2707	119	12	,	,	PUNCT
fcis-2707	119	13	et	et	PROPN
fcis-2707	119	14	al	al	PROPN
fcis-2707	119	15	.	.	PUNCT
fcis-2707	120	1	learning	learn	VERB
fcis-2707	120	2	to	to	PART
fcis-2707	120	3	count	count	VERB
fcis-2707	120	4	via	via	ADP
fcis-2707	120	5	unbalanced	unbalanced	ADJ
fcis-2707	120	6	optimal	optimal	ADJ
fcis-2707	120	7	transport[c]//proceedings	transport[c]//proceeding	NOUN
fcis-2707	120	8	of	of	ADP
fcis-2707	120	9	the	the	DET
fcis-2707	120	10	aaai	aaai	PROPN
fcis-2707	120	11	conference	conference	NOUN
fcis-2707	120	12	on	on	ADP
fcis-2707	120	13	artificial	artificial	ADJ
fcis-2707	120	14	intelligence	intelligence	NOUN
fcis-2707	120	15	.	.	PUNCT
fcis-2707	121	1	2021	2021	NUM
fcis-2707	121	2	,	,	PUNCT
fcis-2707	121	3	35(3	35(3	NUM
fcis-2707	121	4	):	):	PUNCT
fcis-2707	121	5	2319	2319	NUM
fcis-2707	121	6	-	-	SYM
fcis-2707	121	7	2327	2327	NUM
fcis-2707	121	8	.	.	PUNCT
fcis-2707	122	1	[	[	X
fcis-2707	122	2	16	16	NUM
fcis-2707	122	3	]	]	PUNCT
fcis-2707	122	4	xu	xu	PROPN
fcis-2707	123	1	y	y	PROPN
fcis-2707	123	2	,	,	PUNCT
fcis-2707	123	3	zhong	zhong	PROPN
fcis-2707	123	4	z	z	PROPN
fcis-2707	123	5	,	,	PUNCT
fcis-2707	123	6	lian	lian	PROPN
fcis-2707	124	1	d	d	NOUN
fcis-2707	124	2	,	,	PUNCT
fcis-2707	124	3	et	et	PROPN
fcis-2707	124	4	al	al	PROPN
fcis-2707	124	5	.	.	PROPN
fcis-2707	124	6	crowd	crowd	PROPN
fcis-2707	124	7	counting	count	VERB
fcis-2707	124	8	with	with	ADP
fcis-2707	124	9	partial	partial	ADJ
fcis-2707	124	10	annotations	annotation	NOUN
fcis-2707	124	11	in	in	ADP
fcis-2707	124	12	an	an	DET
fcis-2707	124	13	image[c]//proceedings	image[c]//proceeding	NOUN
fcis-2707	124	14	of	of	ADP
fcis-2707	124	15	the	the	DET
fcis-2707	124	16	ieee	ieee	NOUN
fcis-2707	124	17	/	/	SYM
fcis-2707	124	18	cvf	cvf	NOUN
fcis-2707	124	19	international	international	ADJ
fcis-2707	124	20	conference	conference	NOUN
fcis-2707	124	21	on	on	ADP
fcis-2707	124	22	computer	computer	NOUN
fcis-2707	124	23	vision	vision	NOUN
fcis-2707	124	24	.	.	PUNCT
fcis-2707	125	1	2021	2021	NUM
fcis-2707	125	2	:	:	PUNCT
fcis-2707	125	3	1557015579	1557015579	NUM
fcis-2707	125	4	.	.	PUNCT
fcis-2707	126	1	[	[	X
fcis-2707	126	2	17	17	NUM
fcis-2707	126	3	]	]	X
fcis-2707	126	4	chen	chen	PROPN
fcis-2707	126	5	b	b	PROPN
fcis-2707	126	6	,	,	PUNCT
fcis-2707	126	7	yan	yan	PROPN
fcis-2707	127	1	z	z	PROPN
fcis-2707	127	2	,	,	PUNCT
fcis-2707	127	3	li	li	PROPN
fcis-2707	127	4	k	k	PROPN
fcis-2707	127	5	,	,	PUNCT
fcis-2707	127	6	et	et	PROPN
fcis-2707	127	7	al	al	PROPN
fcis-2707	127	8	.	.	PUNCT
fcis-2707	128	1	variational	variational	ADJ
fcis-2707	128	2	attention	attention	NOUN
fcis-2707	128	3	:	:	PUNCT
fcis-2707	128	4	propagating	propagate	VERB
fcis-2707	128	5	domain	domain	NOUN
fcis-2707	128	6	-	-	PUNCT
fcis-2707	128	7	specific	specific	ADJ
fcis-2707	128	8	knowledge	knowledge	NOUN
fcis-2707	128	9	for	for	ADP
fcis-2707	128	10	multi	multi	ADJ
fcis-2707	128	11	-	-	ADJ
fcis-2707	128	12	domain	domain	ADJ
fcis-2707	128	13	learning	learning	NOUN
fcis-2707	128	14	in	in	ADP
fcis-2707	128	15	crowd	crowd	NOUN
fcis-2707	128	16	counting[c]//proceedings	counting[c]//proceeding	NOUN
fcis-2707	128	17	of	of	ADP
fcis-2707	128	18	the	the	DET
fcis-2707	128	19	ieee	ieee	NOUN
fcis-2707	128	20	/	/	SYM
fcis-2707	128	21	cvf	cvf	NOUN
fcis-2707	128	22	international	international	ADJ
fcis-2707	128	23	conference	conference	NOUN
fcis-2707	128	24	on	on	ADP
fcis-2707	128	25	computer	computer	NOUN
fcis-2707	128	26	vision	vision	NOUN
fcis-2707	128	27	.	.	PUNCT
fcis-2707	129	1	2021	2021	NUM
fcis-2707	129	2	:	:	PUNCT
fcis-2707	130	1	1606516075	1606516075	NUM
fcis-2707	130	2	.	.	PUNCT
fcis-2707	131	1	[	[	X
fcis-2707	131	2	18	18	NUM
fcis-2707	131	3	]	]	X
fcis-2707	131	4	cheng	cheng	PROPN
fcis-2707	131	5	j	j	PROPN
fcis-2707	131	6	,	,	PUNCT
fcis-2707	131	7	xiong	xiong	PROPN
fcis-2707	131	8	h	h	PROPN
fcis-2707	131	9	,	,	PUNCT
fcis-2707	131	10	cao	cao	PROPN
fcis-2707	131	11	z	z	PROPN
fcis-2707	131	12	,	,	PUNCT
fcis-2707	131	13	et	et	PROPN
fcis-2707	131	14	al	al	PROPN
fcis-2707	131	15	.	.	PROPN
fcis-2707	131	16	decoupled	decouple	VERB
fcis-2707	131	17	two	two	NUM
fcis-2707	131	18	-	-	PUNCT
fcis-2707	131	19	stage	stage	NOUN
fcis-2707	131	20	crowd	crowd	NOUN
fcis-2707	131	21	counting	counting	NOUN
fcis-2707	131	22	and	and	CCONJ
fcis-2707	131	23	beyond[j	beyond[j	NOUN
fcis-2707	131	24	]	]	PUNCT
fcis-2707	131	25	.	.	PUNCT
fcis-2707	132	1	ieee	ieee	NOUN
fcis-2707	132	2	transactions	transaction	NOUN
fcis-2707	132	3	on	on	ADP
fcis-2707	132	4	image	image	NOUN
fcis-2707	132	5	processing	processing	NOUN
fcis-2707	132	6	,	,	PUNCT
fcis-2707	132	7	2021	2021	NUM
fcis-2707	132	8	,	,	PUNCT
fcis-2707	132	9	30	30	NUM
fcis-2707	132	10	:	:	SYM
fcis-2707	132	11	2862	2862	NUM
fcis-2707	132	12	-	-	SYM
fcis-2707	132	13	2875	2875	NUM
fcis-2707	132	14	.	.	PUNCT