id	sid	tid	token	lemma	pos
ispiv-131	1	1	14th	14th	ADJ
ispiv-131	1	2	international	international	ADJ
ispiv-131	1	3	symposium	symposium	NOUN
ispiv-131	1	4	on	on	ADP
ispiv-131	1	5	particle	particle	NOUN
ispiv-131	1	6	image	image	NOUN
ispiv-131	1	7	velocimetry	velocimetry	NOUN
ispiv-131	1	8	–	–	PUNCT
ispiv-131	1	9	ispiv	ispiv	NOUN
ispiv-131	1	10	2021	2021	NUM
ispiv-131	1	11	august	august	PROPN
ispiv-131	1	12	1–5	1–5	NUM
ispiv-131	1	13	,	,	PUNCT
ispiv-131	1	14	2021	2021	NUM
ispiv-131	1	15	investigating	investigate	VERB
ispiv-131	1	16	optimal	optimal	ADJ
ispiv-131	1	17	training	training	NOUN
ispiv-131	1	18	and	and	CCONJ
ispiv-131	1	19	uncertainty	uncertainty	NOUN
ispiv-131	1	20	quantification	quantification	NOUN
ispiv-131	1	21	for	for	ADP
ispiv-131	1	22	cnn	cnn	PROPN
ispiv-131	1	23	-	-	PUNCT
ispiv-131	1	24	based	base	VERB
ispiv-131	1	25	optical	optical	ADJ
ispiv-131	1	26	flow	flow	NOUN
ispiv-131	1	27	d.	d.	PROPN
ispiv-131	1	28	kurihara1	kurihara1	PROPN
ispiv-131	1	29	,	,	PUNCT
ispiv-131	1	30	g.	g.	PROPN
ispiv-131	1	31	blois1	blois1	PROPN
ispiv-131	1	32	,	,	PUNCT
ispiv-131	1	33	h.	h.	PROPN
ispiv-131	1	34	sakaue1	sakaue1	PROPN
ispiv-131	1	35	,	,	PUNCT
ispiv-131	1	36	d.e	d.e	PROPN
ispiv-131	1	37	.	.	PROPN
ispiv-131	1	38	schiavazzi1,2	schiavazzi1,2	PROPN
ispiv-131	1	39	1	1	NUM
ispiv-131	1	40	university	university	NOUN
ispiv-131	1	41	of	of	ADP
ispiv-131	1	42	notre	notre	PROPN
ispiv-131	1	43	dame	dame	PROPN
ispiv-131	1	44	,	,	PUNCT
ispiv-131	1	45	department	department	NOUN
ispiv-131	1	46	of	of	ADP
ispiv-131	1	47	aerospace	aerospace	NOUN
ispiv-131	1	48	and	and	CCONJ
ispiv-131	1	49	mechanical	mechanical	ADJ
ispiv-131	1	50	engineering	engineering	NOUN
ispiv-131	1	51	,	,	PUNCT
ispiv-131	1	52	notre	notre	PROPN
ispiv-131	1	53	dame	dame	PROPN
ispiv-131	1	54	,	,	PUNCT
ispiv-131	1	55	usa	usa	PROPN
ispiv-131	1	56	2	2	NUM
ispiv-131	1	57	university	university	NOUN
ispiv-131	1	58	of	of	ADP
ispiv-131	1	59	notre	notre	PROPN
ispiv-131	1	60	dame	dame	PROPN
ispiv-131	1	61	,	,	PUNCT
ispiv-131	1	62	department	department	NOUN
ispiv-131	1	63	of	of	ADP
ispiv-131	1	64	applied	applied	ADJ
ispiv-131	1	65	and	and	CCONJ
ispiv-131	1	66	computational	computational	ADJ
ispiv-131	1	67	mathematics	mathematic	NOUN
ispiv-131	1	68	and	and	CCONJ
ispiv-131	1	69	statistics	statistic	NOUN
ispiv-131	1	70	,	,	PUNCT
ispiv-131	1	71	notre	notre	PROPN
ispiv-131	1	72	dame	dame	PROPN
ispiv-131	1	73	,	,	PUNCT
ispiv-131	1	74	usa	usa	PROPN
ispiv-131	1	75	1	1	NUM
ispiv-131	1	76	introduction	introduction	NOUN
ispiv-131	1	77	optical	optical	ADJ
ispiv-131	1	78	flow	flow	NOUN
ispiv-131	1	79	(	(	PUNCT
ispiv-131	1	80	of	of	ADP
ispiv-131	1	81	)	)	PUNCT
ispiv-131	1	82	techniques	technique	NOUN
ispiv-131	1	83	provide	provide	VERB
ispiv-131	1	84	“	"	PUNCT
ispiv-131	1	85	dense	dense	ADJ
ispiv-131	1	86	estimation	estimation	NOUN
ispiv-131	1	87	”	"	PUNCT
ispiv-131	1	88	flow	flow	NOUN
ispiv-131	1	89	maps	map	NOUN
ispiv-131	1	90	(	(	PUNCT
ispiv-131	1	91	i.e.	i.e.	X
ispiv-131	1	92	pixel	pixel	ADJ
ispiv-131	1	93	-	-	PUNCT
ispiv-131	1	94	level	level	NOUN
ispiv-131	1	95	resolution	resolution	NOUN
ispiv-131	1	96	)	)	PUNCT
ispiv-131	1	97	of	of	ADP
ispiv-131	1	98	timecorrelated	timecorrelate	VERB
ispiv-131	1	99	images	image	NOUN
ispiv-131	1	100	and	and	CCONJ
ispiv-131	1	101	thus	thus	ADV
ispiv-131	1	102	are	be	AUX
ispiv-131	1	103	appealing	appeal	VERB
ispiv-131	1	104	to	to	ADP
ispiv-131	1	105	applications	application	NOUN
ispiv-131	1	106	requiring	require	VERB
ispiv-131	1	107	high	high	ADJ
ispiv-131	1	108	spatial	spatial	ADJ
ispiv-131	1	109	resolutions	resolution	NOUN
ispiv-131	1	110	.	.	PUNCT
ispiv-131	2	1	of	of	ADP
ispiv-131	2	2	methods	method	NOUN
ispiv-131	2	3	revolve	revolve	VERB
ispiv-131	2	4	around	around	ADP
ispiv-131	2	5	mathematical	mathematical	ADJ
ispiv-131	2	6	descriptions	description	NOUN
ispiv-131	2	7	of	of	ADP
ispiv-131	2	8	the	the	DET
ispiv-131	2	9	image	image	NOUN
ispiv-131	2	10	as	as	ADP
ispiv-131	2	11	a	a	DET
ispiv-131	2	12	collection	collection	NOUN
ispiv-131	2	13	of	of	ADP
ispiv-131	2	14	features	feature	NOUN
ispiv-131	2	15	,	,	PUNCT
ispiv-131	2	16	in	in	ADP
ispiv-131	2	17	which	which	PRON
ispiv-131	2	18	the	the	DET
ispiv-131	2	19	pixel	pixel	ADJ
ispiv-131	2	20	-	-	PUNCT
ispiv-131	2	21	level	level	NOUN
ispiv-131	2	22	light	light	ADJ
ispiv-131	2	23	intensity	intensity	NOUN
ispiv-131	2	24	is	be	AUX
ispiv-131	2	25	the	the	DET
ispiv-131	2	26	primary	primary	ADJ
ispiv-131	2	27	variable	variable	NOUN
ispiv-131	2	28	(	(	PUNCT
ispiv-131	2	29	horn	horn	NOUN
ispiv-131	2	30	and	and	CCONJ
ispiv-131	2	31	schunck	schunck	ADJ
ispiv-131	2	32	,	,	PUNCT
ispiv-131	2	33	1981	1981	NUM
ispiv-131	2	34	)	)	PUNCT
ispiv-131	2	35	.	.	PUNCT
ispiv-131	3	1	feature	feature	NOUN
ispiv-131	3	2	tracking	tracking	NOUN
ispiv-131	3	3	often	often	ADV
ispiv-131	3	4	involves	involve	VERB
ispiv-131	3	5	the	the	DET
ispiv-131	3	6	notion	notion	NOUN
ispiv-131	3	7	of	of	ADP
ispiv-131	3	8	scale	scale	NOUN
ispiv-131	3	9	invariance	invariance	NOUN
ispiv-131	3	10	.	.	PUNCT
ispiv-131	4	1	traditional	traditional	ADJ
ispiv-131	4	2	of	of	ADP
ispiv-131	4	3	approaches	approach	NOUN
ispiv-131	4	4	,	,	PUNCT
ispiv-131	4	5	merely	merely	ADV
ispiv-131	4	6	based	base	VERB
ispiv-131	4	7	on	on	ADP
ispiv-131	4	8	mathematical	mathematical	ADJ
ispiv-131	4	9	formulations	formulation	NOUN
ispiv-131	4	10	,	,	PUNCT
ispiv-131	4	11	have	have	AUX
ispiv-131	4	12	suffered	suffer	VERB
ispiv-131	4	13	from	from	ADP
ispiv-131	4	14	many	many	ADJ
ispiv-131	4	15	challenges	challenge	NOUN
ispiv-131	4	16	,	,	PUNCT
ispiv-131	4	17	especially	especially	ADV
ispiv-131	4	18	when	when	SCONJ
ispiv-131	4	19	directly	directly	ADV
ispiv-131	4	20	applied	apply	VERB
ispiv-131	4	21	to	to	ADP
ispiv-131	4	22	images	image	NOUN
ispiv-131	4	23	of	of	ADP
ispiv-131	4	24	fluid	fluid	NOUN
ispiv-131	4	25	flows	flow	NOUN
ispiv-131	4	26	textured	texture	VERB
ispiv-131	4	27	with	with	ADP
ispiv-131	4	28	tracer	tracer	NOUN
ispiv-131	4	29	particles	particle	NOUN
ispiv-131	4	30	(	(	PUNCT
ispiv-131	4	31	hereafter	hereafter	ADV
ispiv-131	4	32	piv	piv	NOUN
ispiv-131	4	33	-	-	PUNCT
ispiv-131	4	34	like	like	ADJ
ispiv-131	4	35	images	image	NOUN
ispiv-131	4	36	)	)	PUNCT
ispiv-131	4	37	.	.	PUNCT
ispiv-131	5	1	due	due	ADP
ispiv-131	5	2	to	to	ADP
ispiv-131	5	3	the	the	DET
ispiv-131	5	4	limited	limited	ADJ
ispiv-131	5	5	number	number	NOUN
ispiv-131	5	6	of	of	ADP
ispiv-131	5	7	computationally	computationally	ADV
ispiv-131	5	8	manageable	manageable	ADJ
ispiv-131	5	9	features	feature	NOUN
ispiv-131	5	10	and	and	CCONJ
ispiv-131	5	11	suboptimal	suboptimal	ADJ
ispiv-131	5	12	regularization	regularization	NOUN
ispiv-131	5	13	methods	method	NOUN
ispiv-131	5	14	,	,	PUNCT
ispiv-131	5	15	successful	successful	ADJ
ispiv-131	5	16	implementation	implementation	NOUN
ispiv-131	5	17	of	of	ADP
ispiv-131	5	18	past	past	ADJ
ispiv-131	5	19	approaches	approach	NOUN
ispiv-131	5	20	has	have	AUX
ispiv-131	5	21	been	be	AUX
ispiv-131	5	22	limited	limit	VERB
ispiv-131	5	23	to	to	ADP
ispiv-131	5	24	highly	highly	ADV
ispiv-131	5	25	textured	texture	VERB
ispiv-131	5	26	images	image	NOUN
ispiv-131	5	27	and	and	CCONJ
ispiv-131	5	28	small	small	ADJ
ispiv-131	5	29	displacement	displacement	ADJ
ispiv-131	5	30	dynamic	dynamic	ADJ
ispiv-131	5	31	ranges	range	NOUN
ispiv-131	5	32	.	.	PUNCT
ispiv-131	6	1	recent	recent	ADJ
ispiv-131	6	2	deep	deep	ADJ
ispiv-131	6	3	learning	learning	NOUN
ispiv-131	6	4	-	-	PUNCT
ispiv-131	6	5	based	base	VERB
ispiv-131	6	6	methods	method	NOUN
ispiv-131	6	7	have	have	AUX
ispiv-131	6	8	effectively	effectively	ADV
ispiv-131	6	9	removed	remove	VERB
ispiv-131	6	10	several	several	ADJ
ispiv-131	6	11	limitations	limitation	NOUN
ispiv-131	6	12	,	,	PUNCT
ispiv-131	6	13	offering	offer	VERB
ispiv-131	6	14	an	an	DET
ispiv-131	6	15	opportunity	opportunity	NOUN
ispiv-131	6	16	to	to	PART
ispiv-131	6	17	revitalize	revitalize	VERB
ispiv-131	6	18	of	of	ADP
ispiv-131	6	19	techniques	technique	NOUN
ispiv-131	6	20	.	.	PUNCT
ispiv-131	7	1	being	be	AUX
ispiv-131	7	2	these	these	PRON
ispiv-131	7	3	based	base	VERB
ispiv-131	7	4	on	on	ADP
ispiv-131	7	5	structural	structural	ADJ
ispiv-131	7	6	features	feature	NOUN
ispiv-131	7	7	,	,	PUNCT
ispiv-131	7	8	the	the	DET
ispiv-131	7	9	natural	natural	ADJ
ispiv-131	7	10	ability	ability	NOUN
ispiv-131	7	11	of	of	ADP
ispiv-131	7	12	artificial	artificial	ADJ
ispiv-131	7	13	neural	neural	ADJ
ispiv-131	7	14	networks	network	NOUN
ispiv-131	7	15	(	(	PUNCT
ispiv-131	7	16	ann	ann	PROPN
ispiv-131	7	17	)	)	PUNCT
ispiv-131	7	18	with	with	ADP
ispiv-131	7	19	deep	deep	ADJ
ispiv-131	7	20	architectures	architecture	NOUN
ispiv-131	7	21	to	to	PART
ispiv-131	7	22	extract	extract	VERB
ispiv-131	7	23	a	a	DET
ispiv-131	7	24	large	large	ADJ
ispiv-131	7	25	collection	collection	NOUN
ispiv-131	7	26	of	of	ADP
ispiv-131	7	27	such	such	ADJ
ispiv-131	7	28	features	feature	NOUN
ispiv-131	7	29	at	at	ADP
ispiv-131	7	30	multiple	multiple	ADJ
ispiv-131	7	31	resolutions	resolution	NOUN
ispiv-131	7	32	through	through	ADP
ispiv-131	7	33	convolutions	convolution	NOUN
ispiv-131	7	34	with	with	ADP
ispiv-131	7	35	learnable	learnable	ADJ
ispiv-131	7	36	kernels	kernel	NOUN
ispiv-131	7	37	can	can	AUX
ispiv-131	7	38	be	be	AUX
ispiv-131	7	39	brought	bring	VERB
ispiv-131	7	40	to	to	PART
ispiv-131	7	41	bear	bear	VERB
ispiv-131	7	42	.	.	PUNCT
ispiv-131	8	1	in	in	ADP
ispiv-131	8	2	this	this	DET
ispiv-131	8	3	context	context	NOUN
ispiv-131	8	4	,	,	PUNCT
ispiv-131	8	5	a	a	DET
ispiv-131	8	6	number	number	NOUN
ispiv-131	8	7	of	of	ADP
ispiv-131	8	8	newly	newly	ADV
ispiv-131	8	9	proposed	propose	VERB
ispiv-131	8	10	convolutional	convolutional	ADJ
ispiv-131	8	11	neural	neural	ADJ
ispiv-131	8	12	networks	network	NOUN
ispiv-131	8	13	(	(	PUNCT
ispiv-131	8	14	cnns	cnns	PROPN
ispiv-131	8	15	)	)	PUNCT
ispiv-131	8	16	,	,	PUNCT
ispiv-131	8	17	originally	originally	ADV
ispiv-131	8	18	developed	develop	VERB
ispiv-131	8	19	for	for	ADP
ispiv-131	8	20	computer	computer	NOUN
ispiv-131	8	21	vision	vision	NOUN
ispiv-131	8	22	applications	application	NOUN
ispiv-131	8	23	,	,	PUNCT
ispiv-131	8	24	have	have	AUX
ispiv-131	8	25	been	be	AUX
ispiv-131	8	26	successfully	successfully	ADV
ispiv-131	8	27	applied	apply	VERB
ispiv-131	8	28	to	to	ADP
ispiv-131	8	29	the	the	DET
ispiv-131	8	30	estimation	estimation	NOUN
ispiv-131	8	31	of	of	ADP
ispiv-131	8	32	flows	flow	NOUN
ispiv-131	8	33	from	from	ADP
ispiv-131	8	34	dynamic	dynamic	ADJ
ispiv-131	8	35	scenes	scene	NOUN
ispiv-131	8	36	with	with	ADP
ispiv-131	8	37	moving	move	VERB
ispiv-131	8	38	objects	object	NOUN
ispiv-131	8	39	.	.	PUNCT
ispiv-131	9	1	a	a	DET
ispiv-131	9	2	recent	recent	ADJ
ispiv-131	9	3	example	example	NOUN
ispiv-131	9	4	is	be	AUX
ispiv-131	9	5	liteflownet	liteflownet	PROPN
ispiv-131	9	6	(	(	PUNCT
ispiv-131	9	7	fig	fig	NOUN
ispiv-131	9	8	.	.	PUNCT
ispiv-131	10	1	1(a	1(a	NUM
ispiv-131	10	2	)	)	PUNCT
ispiv-131	10	3	)	)	PUNCT
ispiv-131	11	1	,	,	PUNCT
ispiv-131	11	2	which	which	PRON
ispiv-131	11	3	provides	provide	VERB
ispiv-131	11	4	state	state	NOUN
ispiv-131	11	5	-	-	PUNCT
ispiv-131	11	6	of	of	ADP
ispiv-131	11	7	-	-	PUNCT
ispiv-131	11	8	the	the	DET
ispiv-131	11	9	-	-	PUNCT
ispiv-131	11	10	art	art	NOUN
ispiv-131	11	11	performance	performance	NOUN
ispiv-131	11	12	on	on	ADP
ispiv-131	11	13	a	a	DET
ispiv-131	11	14	number	number	NOUN
ispiv-131	11	15	of	of	ADP
ispiv-131	11	16	datasets	dataset	NOUN
ispiv-131	11	17	including	include	VERB
ispiv-131	11	18	rigid	rigid	ADJ
ispiv-131	11	19	body	body	NOUN
ispiv-131	11	20	motion	motion	NOUN
ispiv-131	11	21	of	of	ADP
ispiv-131	11	22	objects	object	NOUN
ispiv-131	11	23	in	in	ADP
ispiv-131	11	24	space	space	NOUN
ispiv-131	11	25	,	,	PUNCT
ispiv-131	11	26	vehicles	vehicle	NOUN
ispiv-131	11	27	moving	move	VERB
ispiv-131	11	28	in	in	ADP
ispiv-131	11	29	traffic	traffic	NOUN
ispiv-131	11	30	and	and	CCONJ
ispiv-131	11	31	,	,	PUNCT
ispiv-131	11	32	most	most	ADV
ispiv-131	11	33	notably	notably	ADV
ispiv-131	11	34	,	,	PUNCT
ispiv-131	11	35	computer	computer	NOUN
ispiv-131	11	36	animated	animate	VERB
ispiv-131	11	37	sequences	sequence	NOUN
ispiv-131	11	38	(	(	PUNCT
ispiv-131	11	39	hui	hui	PROPN
ispiv-131	11	40	et	et	PROPN
ispiv-131	11	41	al	al	PROPN
ispiv-131	11	42	.	.	PROPN
ispiv-131	11	43	,	,	PUNCT
ispiv-131	11	44	2018	2018	NUM
ispiv-131	11	45	)	)	PUNCT
ispiv-131	11	46	.	.	PUNCT
ispiv-131	12	1	however	however	ADV
ispiv-131	12	2	,	,	PUNCT
ispiv-131	12	3	there	there	PRON
ispiv-131	12	4	is	be	VERB
ispiv-131	12	5	still	still	ADV
ispiv-131	12	6	limited	limited	ADJ
ispiv-131	12	7	understanding	understanding	NOUN
ispiv-131	12	8	of	of	ADP
ispiv-131	12	9	which	which	DET
ispiv-131	12	10	network	network	NOUN
ispiv-131	12	11	setup	setup	NOUN
ispiv-131	12	12	(	(	PUNCT
ispiv-131	12	13	e.g.	e.g.	ADV
ispiv-131	12	14	architecture	architecture	NOUN
ispiv-131	12	15	,	,	PUNCT
ispiv-131	12	16	hyperparameter	hyperparameter	NOUN
ispiv-131	12	17	selection	selection	NOUN
ispiv-131	12	18	,	,	PUNCT
ispiv-131	12	19	etc	etc	X
ispiv-131	12	20	.	.	X
ispiv-131	12	21	)	)	PUNCT
ispiv-131	12	22	provides	provide	VERB
ispiv-131	12	23	optimal	optimal	ADJ
ispiv-131	12	24	flow	flow	NOUN
ispiv-131	12	25	accuracy	accuracy	NOUN
ispiv-131	12	26	for	for	ADP
ispiv-131	12	27	piv	piv	NOUN
ispiv-131	12	28	-	-	PUNCT
ispiv-131	12	29	like	like	ADJ
ispiv-131	12	30	images	image	NOUN
ispiv-131	12	31	.	.	PUNCT
ispiv-131	13	1	in	in	ADP
ispiv-131	13	2	this	this	DET
ispiv-131	13	3	context	context	NOUN
ispiv-131	13	4	,	,	PUNCT
ispiv-131	13	5	the	the	DET
ispiv-131	13	6	goal	goal	NOUN
ispiv-131	13	7	of	of	ADP
ispiv-131	13	8	this	this	DET
ispiv-131	13	9	study	study	NOUN
ispiv-131	13	10	is	be	AUX
ispiv-131	13	11	to	to	ADP
ispiv-131	13	12	1	1	NUM
ispiv-131	13	13	)	)	PUNCT
ispiv-131	13	14	provide	provide	VERB
ispiv-131	13	15	a	a	DET
ispiv-131	13	16	quantitative	quantitative	ADJ
ispiv-131	13	17	understanding	understanding	NOUN
ispiv-131	13	18	of	of	ADP
ispiv-131	13	19	how	how	SCONJ
ispiv-131	13	20	liteflownet	liteflownet	NOUN
ispiv-131	13	21	performs	perform	VERB
ispiv-131	13	22	for	for	ADP
ispiv-131	13	23	piv	piv	NOUN
ispiv-131	13	24	-	-	PUNCT
ispiv-131	13	25	like	like	ADJ
ispiv-131	13	26	images	image	NOUN
ispiv-131	13	27	under	under	ADP
ispiv-131	13	28	different	different	ADJ
ispiv-131	13	29	training	training	NOUN
ispiv-131	13	30	paradigms	paradigm	NOUN
ispiv-131	13	31	and	and	CCONJ
ispiv-131	13	32	hyperparameter	hyperparameter	NOUN
ispiv-131	13	33	setups	setup	NOUN
ispiv-131	13	34	,	,	PUNCT
ispiv-131	13	35	and	and	CCONJ
ispiv-131	13	36	also	also	ADV
ispiv-131	13	37	to	to	ADP
ispiv-131	13	38	2	2	NUM
ispiv-131	13	39	)	)	PUNCT
ispiv-131	13	40	extended	extend	VERB
ispiv-131	13	41	the	the	DET
ispiv-131	13	42	capabilities	capability	NOUN
ispiv-131	13	43	of	of	ADP
ispiv-131	13	44	liteflownet	liteflownet	NOUN
ispiv-131	13	45	to	to	PART
ispiv-131	13	46	quantify	quantify	VERB
ispiv-131	13	47	flow	flow	NOUN
ispiv-131	13	48	uncertainty	uncertainty	NOUN
ispiv-131	13	49	.	.	PUNCT
ispiv-131	14	1	2	2	NUM
ispiv-131	14	2	methods	method	NOUN
ispiv-131	14	3	liteflownet	liteflownet	NOUN
ispiv-131	14	4	is	be	AUX
ispiv-131	14	5	a	a	DET
ispiv-131	14	6	family	family	NOUN
ispiv-131	14	7	of	of	ADP
ispiv-131	14	8	recently	recently	ADV
ispiv-131	14	9	proposed	propose	VERB
ispiv-131	14	10	deep	deep	ADJ
ispiv-131	14	11	neural	neural	ADJ
ispiv-131	14	12	networks	network	NOUN
ispiv-131	14	13	for	for	ADP
ispiv-131	14	14	optical	optical	ADJ
ispiv-131	14	15	flow	flow	NOUN
ispiv-131	14	16	estimation	estimation	NOUN
ispiv-131	14	17	(	(	PUNCT
ispiv-131	14	18	hui	hui	PROPN
ispiv-131	14	19	et	et	PROPN
ispiv-131	14	20	al	al	PROPN
ispiv-131	14	21	.	.	PROPN
ispiv-131	14	22	,	,	PUNCT
ispiv-131	14	23	2018	2018	NUM
ispiv-131	14	24	,	,	PUNCT
ispiv-131	14	25	2020	2020	NUM
ispiv-131	14	26	)	)	PUNCT
ispiv-131	14	27	.	.	PUNCT
ispiv-131	15	1	its	its	PRON
ispiv-131	15	2	architecture	architecture	NOUN
ispiv-131	15	3	consists	consist	VERB
ispiv-131	15	4	of	of	ADP
ispiv-131	15	5	pyramidal	pyramidal	ADJ
ispiv-131	15	6	feature	feature	NOUN
ispiv-131	15	7	extraction	extraction	NOUN
ispiv-131	15	8	(	(	PUNCT
ispiv-131	15	9	netc	netc	NOUN
ispiv-131	15	10	)	)	PUNCT
ispiv-131	15	11	followed	follow	VERB
ispiv-131	15	12	by	by	ADP
ispiv-131	15	13	a	a	DET
ispiv-131	15	14	cascade	cascade	NOUN
ispiv-131	15	15	of	of	ADP
ispiv-131	15	16	flow	flow	NOUN
ispiv-131	15	17	inference	inference	NOUN
ispiv-131	15	18	modules	module	NOUN
ispiv-131	15	19	(	(	PUNCT
ispiv-131	15	20	nete	nete	ADJ
ispiv-131	15	21	)	)	PUNCT
ispiv-131	15	22	,	,	PUNCT
ispiv-131	15	23	i.e.	i.e.	X
ispiv-131	15	24	,	,	PUNCT
ispiv-131	15	25	a	a	DET
ispiv-131	15	26	matching	matching	NOUN
ispiv-131	15	27	module	module	NOUN
ispiv-131	15	28	,	,	PUNCT
ispiv-131	15	29	a	a	DET
ispiv-131	15	30	subpixel	subpixel	NOUN
ispiv-131	15	31	module	module	NOUN
ispiv-131	15	32	,	,	PUNCT
ispiv-131	15	33	and	and	CCONJ
ispiv-131	15	34	a	a	DET
ispiv-131	15	35	regularization	regularization	NOUN
ispiv-131	15	36	module	module	NOUN
ispiv-131	15	37	.	.	PUNCT
ispiv-131	16	1	the	the	DET
ispiv-131	16	2	matching	matching	NOUN
ispiv-131	16	3	module	module	NOUN
ispiv-131	16	4	identifies	identify	VERB
ispiv-131	16	5	the	the	DET
ispiv-131	16	6	corresponding	correspond	VERB
ispiv-131	16	7	features	feature	NOUN
ispiv-131	16	8	in	in	ADP
ispiv-131	16	9	the	the	DET
ispiv-131	16	10	image	image	NOUN
ispiv-131	16	11	pair	pair	NOUN
ispiv-131	16	12	,	,	PUNCT
ispiv-131	16	13	the	the	DET
ispiv-131	16	14	subpixel	subpixel	ADJ
ispiv-131	16	15	module	module	NOUN
ispiv-131	16	16	corrects	correct	VERB
ispiv-131	16	17	the	the	DET
ispiv-131	16	18	flow	flow	NOUN
ispiv-131	16	19	estimation	estimation	NOUN
ispiv-131	16	20	and	and	CCONJ
ispiv-131	16	21	provides	provide	VERB
ispiv-131	16	22	subpixel	subpixel	ADJ
ispiv-131	16	23	accuracy	accuracy	NOUN
ispiv-131	16	24	,	,	PUNCT
ispiv-131	16	25	whereas	whereas	SCONJ
ispiv-131	16	26	the	the	DET
ispiv-131	16	27	regularization	regularization	NOUN
ispiv-131	16	28	module	module	NOUN
ispiv-131	16	29	is	be	AUX
ispiv-131	16	30	used	use	VERB
ispiv-131	16	31	to	to	PART
ispiv-131	16	32	refine	refine	VERB
ispiv-131	16	33	the	the	DET
ispiv-131	16	34	flow	flow	NOUN
ispiv-131	16	35	estimate	estimate	NOUN
ispiv-131	16	36	near	near	ADP
ispiv-131	16	37	the	the	DET
ispiv-131	16	38	boundary	boundary	NOUN
ispiv-131	16	39	of	of	ADP
ispiv-131	16	40	moving	move	VERB
ispiv-131	16	41	objects	object	NOUN
ispiv-131	16	42	.	.	PUNCT
ispiv-131	17	1	the	the	DET
ispiv-131	17	2	network	network	NOUN
ispiv-131	17	3	progressively	progressively	ADV
ispiv-131	17	4	identifies	identify	VERB
ispiv-131	17	5	flow	flow	NOUN
ispiv-131	17	6	features	feature	NOUN
ispiv-131	17	7	in	in	ADP
ispiv-131	17	8	a	a	DET
ispiv-131	17	9	coarse	coarse	NOUN
ispiv-131	17	10	-	-	PUNCT
ispiv-131	17	11	to	to	ADP
ispiv-131	17	12	-	-	PUNCT
ispiv-131	17	13	fine	fine	ADJ
ispiv-131	17	14	resolution	resolution	NOUN
ispiv-131	17	15	pipeline	pipeline	NOUN
ispiv-131	17	16	,	,	PUNCT
ispiv-131	17	17	starting	start	VERB
ispiv-131	17	18	from	from	ADP
ispiv-131	17	19	level	level	NOUN
ispiv-131	17	20	6	6	NUM
ispiv-131	17	21	(	(	PUNCT
ispiv-131	17	22	coarser	coarse	ADJ
ispiv-131	17	23	resolution	resolution	NOUN
ispiv-131	17	24	)	)	PUNCT
ispiv-131	17	25	to	to	PART
ispiv-131	17	26	level	level	VERB
ispiv-131	17	27	2	2	NUM
ispiv-131	17	28	(	(	PUNCT
ispiv-131	17	29	finer	fine	ADJ
ispiv-131	17	30	resolution	resolution	NOUN
ispiv-131	17	31	)	)	PUNCT
ispiv-131	17	32	.	.	PUNCT
ispiv-131	18	1	the	the	DET
ispiv-131	18	2	original	original	ADJ
ispiv-131	18	3	liteflownet	liteflownet	NOUN
ispiv-131	18	4	was	be	AUX
ispiv-131	18	5	trained	train	VERB
ispiv-131	18	6	using	use	VERB
ispiv-131	18	7	a	a	DET
ispiv-131	18	8	staged	stage	VERB
ispiv-131	18	9	process	process	NOUN
ispiv-131	18	10	(	(	PUNCT
ispiv-131	18	11	see	see	VERB
ispiv-131	18	12	fig	fig	NOUN
ispiv-131	18	13	.	.	PUNCT
ispiv-131	19	1	1(a	1(a	NUM
ispiv-131	19	2	)	)	PUNCT
ispiv-131	19	3	)	)	PUNCT
ispiv-131	19	4	,	,	PUNCT
ispiv-131	19	5	and	and	CCONJ
ispiv-131	19	6	did	do	AUX
ispiv-131	19	7	not	not	PART
ispiv-131	19	8	support	support	VERB
ispiv-131	19	9	quantification	quantification	NOUN
ispiv-131	19	10	of	of	ADP
ispiv-131	19	11	flow	flow	NOUN
ispiv-131	19	12	uncertainty	uncertainty	NOUN
ispiv-131	19	13	.	.	PUNCT
ispiv-131	20	1	the	the	DET
ispiv-131	20	2	first	first	ADJ
ispiv-131	20	3	portion	portion	NOUN
ispiv-131	20	4	of	of	ADP
ispiv-131	20	5	this	this	DET
ispiv-131	20	6	work	work	NOUN
ispiv-131	20	7	assesses	assess	VERB
ispiv-131	20	8	the	the	DET
ispiv-131	20	9	predictive	predictive	ADJ
ispiv-131	20	10	performance	performance	NOUN
ispiv-131	20	11	of	of	ADP
ispiv-131	20	12	liteflownet	liteflownet	NOUN
ispiv-131	20	13	using	use	VERB
ispiv-131	20	14	available	available	ADJ
ispiv-131	20	15	pre	pre	ADJ
ispiv-131	20	16	-	-	ADJ
ispiv-131	20	17	trained	train	VERB
ispiv-131	20	18	weights	weight	NOUN
ispiv-131	20	19	.	.	PUNCT
ispiv-131	21	1	tests	test	NOUN
ispiv-131	21	2	targeted	target	VERB
ispiv-131	21	3	synthetic	synthetic	ADJ
ispiv-131	21	4	piv	piv	NOUN
ispiv-131	21	5	-	-	PUNCT
ispiv-131	21	6	like	like	ADJ
ispiv-131	21	7	image	image	NOUN
ispiv-131	21	8	sets	set	NOUN
ispiv-131	21	9	with	with	ADP
ispiv-131	21	10	varying	vary	VERB
ispiv-131	21	11	particle	particle	NOUN
ispiv-131	21	12	density	density	NOUN
ispiv-131	21	13	,	,	PUNCT
ispiv-131	21	14	size	size	NOUN
ispiv-131	21	15	and	and	CCONJ
ispiv-131	21	16	displacement	displacement	NOUN
ispiv-131	21	17	.	.	PUNCT
ispiv-131	22	1	we	we	PRON
ispiv-131	22	2	then	then	ADV
ispiv-131	22	3	explored	explore	VERB
ispiv-131	22	4	the	the	DET
ispiv-131	22	5	potential	potential	NOUN
ispiv-131	22	6	of	of	ADP
ispiv-131	22	7	liteflownet	liteflownet	PROPN
ispiv-131	22	8	when	when	SCONJ
ispiv-131	22	9	trained	train	VERB
ispiv-131	22	10	from	from	ADP
ispiv-131	22	11	piv	piv	NOUN
ispiv-131	22	12	-	-	PUNCT
ispiv-131	22	13	specific	specific	ADJ
ispiv-131	22	14	examples	example	NOUN
ispiv-131	22	15	,	,	PUNCT
ispiv-131	22	16	following	follow	VERB
ispiv-131	22	17	two	two	NUM
ispiv-131	22	18	different	different	ADJ
ispiv-131	22	19	training	training	NOUN
ispiv-131	22	20	paradigms	paradigm	NOUN
ispiv-131	22	21	proposed	propose	VERB
ispiv-131	22	22	in	in	ADP
ispiv-131	22	23	the	the	DET
ispiv-131	22	24	literature	literature	NOUN
ispiv-131	22	25	.	.	PUNCT
ispiv-131	23	1	in	in	ADP
ispiv-131	23	2	addition	addition	NOUN
ispiv-131	23	3	,	,	PUNCT
ispiv-131	23	4	we	we	PRON
ispiv-131	23	5	augmented	augment	VERB
ispiv-131	23	6	the	the	DET
ispiv-131	23	7	liteflownet	liteflownet	NOUN
ispiv-131	23	8	architecture	architecture	NOUN
ispiv-131	23	9	with	with	ADP
ispiv-131	23	10	dropout	dropout	NOUN
ispiv-131	23	11	layers	layer	NOUN
ispiv-131	23	12	providing	provide	VERB
ispiv-131	23	13	both	both	DET
ispiv-131	23	14	a	a	DET
ispiv-131	23	15	regularization	regularization	NOUN
ispiv-131	23	16	mechanism	mechanism	NOUN
ispiv-131	23	17	and	and	CCONJ
ispiv-131	23	18	the	the	DET
ispiv-131	23	19	possibility	possibility	NOUN
ispiv-131	23	20	to	to	PART
ispiv-131	23	21	estimate	estimate	VERB
ispiv-131	23	22	uncertainty	uncertainty	NOUN
ispiv-131	23	23	from	from	ADP
ispiv-131	23	24	prediction	prediction	NOUN
ispiv-131	23	25	ensembles	ensemble	NOUN
ispiv-131	23	26	.	.	PUNCT
ispiv-131	24	1	figure	figure	NOUN
ispiv-131	24	2	1	1	NUM
ispiv-131	24	3	:	:	PUNCT
ispiv-131	24	4	(	(	PUNCT
ispiv-131	24	5	left	left	ADJ
ispiv-131	24	6	)	)	PUNCT
ispiv-131	24	7	liteflownet	liteflownet	NOUN
ispiv-131	24	8	architecture	architecture	NOUN
ispiv-131	24	9	and	and	CCONJ
ispiv-131	24	10	schematics	schematic	NOUN
ispiv-131	24	11	of	of	ADP
ispiv-131	24	12	a	a	DET
ispiv-131	24	13	staged	stage	VERB
ispiv-131	24	14	training	training	NOUN
ispiv-131	24	15	sequence	sequence	NOUN
ispiv-131	24	16	.	.	PUNCT
ispiv-131	25	1	(	(	PUNCT
ispiv-131	25	2	right	right	ADJ
ispiv-131	25	3	)	)	PUNCT
ispiv-131	25	4	prediction	prediction	NOUN
ispiv-131	25	5	of	of	ADP
ispiv-131	25	6	instantaneous	instantaneous	ADJ
ispiv-131	25	7	flow	flow	NOUN
ispiv-131	25	8	fields	field	NOUN
ispiv-131	25	9	:	:	PUNCT
ispiv-131	25	10	the	the	DET
ispiv-131	25	11	first	first	ADJ
ispiv-131	25	12	row	row	NOUN
ispiv-131	25	13	(	(	PUNCT
ispiv-131	25	14	gt	gt	INTJ
ispiv-131	25	15	)	)	PUNCT
ispiv-131	25	16	refers	refer	VERB
ispiv-131	25	17	to	to	ADP
ispiv-131	25	18	the	the	DET
ispiv-131	25	19	ground	ground	NOUN
ispiv-131	25	20	truth	truth	NOUN
ispiv-131	25	21	.	.	PUNCT
ispiv-131	26	1	predictions	prediction	NOUN
ispiv-131	26	2	are	be	AUX
ispiv-131	26	3	obtained	obtain	VERB
ispiv-131	26	4	from	from	ADP
ispiv-131	26	5	end	end	NOUN
ispiv-131	26	6	-	-	PUNCT
ispiv-131	26	7	to	to	ADP
ispiv-131	26	8	-	-	PUNCT
ispiv-131	26	9	end	end	NOUN
ispiv-131	26	10	training	training	NOUN
ispiv-131	26	11	with	with	ADP
ispiv-131	26	12	dropouts	dropout	NOUN
ispiv-131	26	13	(	(	PUNCT
ispiv-131	26	14	p1	p1	NOUN
ispiv-131	26	15	)	)	PUNCT
ispiv-131	26	16	and	and	CCONJ
ispiv-131	26	17	with	with	ADP
ispiv-131	26	18	optimal	optimal	ADJ
ispiv-131	26	19	loss	loss	NOUN
ispiv-131	26	20	penalties	penalty	NOUN
ispiv-131	26	21	from	from	ADP
ispiv-131	26	22	all	all	DET
ispiv-131	26	23	levels	level	NOUN
ispiv-131	26	24	(	(	PUNCT
ispiv-131	26	25	row	row	NOUN
ispiv-131	26	26	p2	p2	NOUN
ispiv-131	26	27	)	)	PUNCT
ispiv-131	26	28	.	.	PUNCT
ispiv-131	27	1	standard	standard	ADJ
ispiv-131	27	2	deviations	deviation	NOUN
ispiv-131	27	3	from	from	ADP
ispiv-131	27	4	ensemble	ensemble	ADJ
ispiv-131	27	5	predictions	prediction	NOUN
ispiv-131	27	6	for	for	ADP
ispiv-131	27	7	p1	p1	NOUN
ispiv-131	27	8	and	and	CCONJ
ispiv-131	27	9	p2	p2	PROPN
ispiv-131	27	10	are	be	AUX
ispiv-131	27	11	shown	show	VERB
ispiv-131	27	12	in	in	ADP
ispiv-131	27	13	u1	u1	NOUN
ispiv-131	27	14	and	and	CCONJ
ispiv-131	27	15	u2	u2	NOUN
ispiv-131	27	16	,	,	PUNCT
ispiv-131	27	17	respectively	respectively	ADV
ispiv-131	27	18	.	.	PUNCT
ispiv-131	28	1	3	3	NUM
ispiv-131	28	2	results	result	NOUN
ispiv-131	28	3	first	first	ADV
ispiv-131	28	4	,	,	PUNCT
ispiv-131	28	5	three	three	NUM
ispiv-131	28	6	sets	set	NOUN
ispiv-131	28	7	of	of	ADP
ispiv-131	28	8	weights	weight	NOUN
ispiv-131	28	9	were	be	AUX
ispiv-131	28	10	tested	test	VERB
ispiv-131	28	11	(	(	PUNCT
ispiv-131	28	12	referred	refer	VERB
ispiv-131	28	13	to	to	ADP
ispiv-131	28	14	as	as	ADP
ispiv-131	28	15	default	default	NOUN
ispiv-131	28	16	,	,	PUNCT
ispiv-131	28	17	kitti	kitti	PROPN
ispiv-131	28	18	and	and	CCONJ
ispiv-131	28	19	sintel	sintel	NOUN
ispiv-131	28	20	)	)	PUNCT
ispiv-131	28	21	,	,	PUNCT
ispiv-131	28	22	and	and	CCONJ
ispiv-131	28	23	their	their	PRON
ispiv-131	28	24	predictions	prediction	NOUN
ispiv-131	28	25	compared	compare	VERB
ispiv-131	28	26	against	against	ADP
ispiv-131	28	27	piv	piv	NOUN
ispiv-131	28	28	image	image	NOUN
ispiv-131	28	29	processing	processing	NOUN
ispiv-131	28	30	using	use	VERB
ispiv-131	28	31	three	three	NUM
ispiv-131	28	32	interrogation	interrogation	NOUN
ispiv-131	28	33	window	window	NOUN
ispiv-131	28	34	sizes	size	NOUN
ispiv-131	28	35	(	(	PUNCT
ispiv-131	28	36	64	64	NUM
ispiv-131	28	37	,	,	PUNCT
ispiv-131	28	38	32	32	NUM
ispiv-131	28	39	,	,	PUNCT
ispiv-131	28	40	and	and	CCONJ
ispiv-131	28	41	16	16	NUM
ispiv-131	28	42	)	)	PUNCT
ispiv-131	28	43	,	,	PUNCT
ispiv-131	28	44	with	with	ADP
ispiv-131	28	45	50	50	NUM
ispiv-131	28	46	%	%	NOUN
ispiv-131	28	47	overlap	overlap	NOUN
ispiv-131	28	48	.	.	PUNCT
ispiv-131	29	1	the	the	DET
ispiv-131	29	2	comparisons	comparison	NOUN
ispiv-131	29	3	were	be	AUX
ispiv-131	29	4	made	make	VERB
ispiv-131	29	5	by	by	ADP
ispiv-131	29	6	statistical	statistical	ADJ
ispiv-131	29	7	analysis	analysis	NOUN
ispiv-131	29	8	of	of	ADP
ispiv-131	29	9	large	large	ADJ
ispiv-131	29	10	samples	sample	NOUN
ispiv-131	29	11	,	,	PUNCT
ispiv-131	29	12	using	use	VERB
ispiv-131	29	13	average	average	ADJ
ispiv-131	29	14	absolute	absolute	ADJ
ispiv-131	29	15	pixel	pixel	NOUN
ispiv-131	29	16	differences	difference	NOUN
ispiv-131	29	17	under	under	ADP
ispiv-131	29	18	different	different	ADJ
ispiv-131	29	19	upand	upand	NOUN
ispiv-131	29	20	down	down	ADV
ispiv-131	29	21	-	-	PUNCT
ispiv-131	29	22	scaling	scale	VERB
ispiv-131	29	23	interpolation	interpolation	NOUN
ispiv-131	29	24	strategies	strategy	NOUN
ispiv-131	29	25	.	.	PUNCT
ispiv-131	30	1	sintel	sintel	NOUN
ispiv-131	30	2	weights	weight	NOUN
ispiv-131	30	3	offered	offer	VERB
ispiv-131	30	4	the	the	DET
ispiv-131	30	5	best	good	ADJ
ispiv-131	30	6	performance	performance	NOUN
ispiv-131	30	7	due	due	ADP
ispiv-131	30	8	to	to	ADP
ispiv-131	30	9	the	the	DET
ispiv-131	30	10	presence	presence	NOUN
ispiv-131	30	11	of	of	ADP
ispiv-131	30	12	image	image	NOUN
ispiv-131	30	13	deformation	deformation	NOUN
ispiv-131	30	14	and	and	CCONJ
ispiv-131	30	15	shear	shear	NOUN
ispiv-131	30	16	in	in	ADP
ispiv-131	30	17	the	the	DET
ispiv-131	30	18	training	training	NOUN
ispiv-131	30	19	dataset	dataset	NOUN
ispiv-131	30	20	,	,	PUNCT
ispiv-131	30	21	unlike	unlike	ADP
ispiv-131	30	22	default	default	NOUN
ispiv-131	30	23	and	and	CCONJ
ispiv-131	30	24	kitti	kitti	PROPN
ispiv-131	30	25	which	which	PRON
ispiv-131	30	26	are	be	AUX
ispiv-131	30	27	mainly	mainly	ADV
ispiv-131	30	28	trained	train	VERB
ispiv-131	30	29	from	from	ADP
ispiv-131	30	30	rigidly	rigidly	ADV
ispiv-131	30	31	moving	move	VERB
ispiv-131	30	32	examples	example	NOUN
ispiv-131	30	33	.	.	PUNCT
ispiv-131	31	1	sintel	sintel	NOUN
ispiv-131	31	2	results	result	NOUN
ispiv-131	31	3	were	be	AUX
ispiv-131	31	4	comparable	comparable	ADJ
ispiv-131	31	5	to	to	ADP
ispiv-131	31	6	those	those	PRON
ispiv-131	31	7	obtained	obtain	VERB
ispiv-131	31	8	using	use	VERB
ispiv-131	31	9	piv	piv	NOUN
ispiv-131	31	10	correlations	correlation	NOUN
ispiv-131	31	11	.	.	PUNCT
ispiv-131	32	1	the	the	DET
ispiv-131	32	2	first	first	ADJ
ispiv-131	32	3	newly	newly	ADV
ispiv-131	32	4	tested	test	VERB
ispiv-131	32	5	training	training	NOUN
ispiv-131	32	6	approach	approach	NOUN
ispiv-131	32	7	consisted	consist	VERB
ispiv-131	32	8	of	of	ADP
ispiv-131	32	9	multiple	multiple	ADJ
ispiv-131	32	10	sessions	session	NOUN
ispiv-131	32	11	where	where	SCONJ
ispiv-131	32	12	finer	fine	ADJ
ispiv-131	32	13	image	image	NOUN
ispiv-131	32	14	resolution	resolution	NOUN
ispiv-131	32	15	levels	level	NOUN
ispiv-131	32	16	are	be	AUX
ispiv-131	32	17	progressively	progressively	ADV
ispiv-131	32	18	activated	activate	VERB
ispiv-131	32	19	at	at	ADP
ispiv-131	32	20	each	each	DET
ispiv-131	32	21	successive	successive	ADJ
ispiv-131	32	22	stage	stage	NOUN
ispiv-131	32	23	(	(	PUNCT
ispiv-131	32	24	staged	stage	VERB
ispiv-131	32	25	training	training	NOUN
ispiv-131	32	26	,	,	PUNCT
ispiv-131	32	27	see	see	VERB
ispiv-131	32	28	fig	fig	NOUN
ispiv-131	32	29	.	.	PUNCT
ispiv-131	33	1	1(a	1(a	NUM
ispiv-131	33	2	)	)	PUNCT
ispiv-131	33	3	)	)	PUNCT
ispiv-131	33	4	.	.	PUNCT
ispiv-131	34	1	the	the	DET
ispiv-131	34	2	second	second	ADJ
ispiv-131	34	3	is	be	AUX
ispiv-131	34	4	referred	refer	VERB
ispiv-131	34	5	to	to	ADP
ispiv-131	34	6	as	as	ADP
ispiv-131	34	7	end	end	NOUN
ispiv-131	34	8	-	-	PUNCT
ispiv-131	34	9	to	to	ADP
ispiv-131	34	10	-	-	PUNCT
ispiv-131	34	11	end	end	NOUN
ispiv-131	34	12	training	training	NOUN
ispiv-131	34	13	,	,	PUNCT
ispiv-131	34	14	where	where	SCONJ
ispiv-131	34	15	the	the	DET
ispiv-131	34	16	complete	complete	ADJ
ispiv-131	34	17	network	network	NOUN
ispiv-131	34	18	is	be	AUX
ispiv-131	34	19	trained	train	VERB
ispiv-131	34	20	all	all	ADV
ispiv-131	34	21	at	at	ADP
ispiv-131	34	22	once	once	ADV
ispiv-131	34	23	,	,	PUNCT
ispiv-131	34	24	and	and	CCONJ
ispiv-131	34	25	the	the	DET
ispiv-131	34	26	loss	loss	NOUN
ispiv-131	34	27	is	be	AUX
ispiv-131	34	28	calculated	calculate	VERB
ispiv-131	34	29	as	as	ADP
ispiv-131	34	30	a	a	DET
ispiv-131	34	31	penalized	penalize	VERB
ispiv-131	34	32	aggregation	aggregation	NOUN
ispiv-131	34	33	of	of	ADP
ispiv-131	34	34	prediction	prediction	NOUN
ispiv-131	34	35	errors	error	NOUN
ispiv-131	34	36	from	from	ADP
ispiv-131	34	37	all	all	DET
ispiv-131	34	38	levels	level	NOUN
ispiv-131	34	39	.	.	PUNCT
ispiv-131	35	1	end	end	NOUN
ispiv-131	35	2	-	-	PUNCT
ispiv-131	35	3	to	to	ADP
ispiv-131	35	4	-	-	PUNCT
ispiv-131	35	5	end	end	NOUN
ispiv-131	35	6	training	training	NOUN
ispiv-131	35	7	generally	generally	ADV
ispiv-131	35	8	produces	produce	VERB
ispiv-131	35	9	both	both	CCONJ
ispiv-131	35	10	minimal	minimal	ADJ
ispiv-131	35	11	losses	loss	NOUN
ispiv-131	35	12	and	and	CCONJ
ispiv-131	35	13	best	good	ADJ
ispiv-131	35	14	accuracy	accuracy	NOUN
ispiv-131	35	15	.	.	PUNCT
ispiv-131	36	1	however	however	ADV
ispiv-131	36	2	,	,	PUNCT
ispiv-131	36	3	it	it	PRON
ispiv-131	36	4	is	be	AUX
ispiv-131	36	5	less	less	ADV
ispiv-131	36	6	clear	clear	ADJ
ispiv-131	36	7	how	how	SCONJ
ispiv-131	36	8	to	to	PART
ispiv-131	36	9	weight	weight	VERB
ispiv-131	36	10	the	the	DET
ispiv-131	36	11	losses	loss	NOUN
ispiv-131	36	12	from	from	ADP
ispiv-131	36	13	each	each	DET
ispiv-131	36	14	level	level	NOUN
ispiv-131	36	15	,	,	PUNCT
ispiv-131	36	16	particularly	particularly	ADV
ispiv-131	36	17	for	for	ADP
ispiv-131	36	18	a	a	DET
ispiv-131	36	19	general	general	ADJ
ispiv-131	36	20	system	system	NOUN
ispiv-131	36	21	which	which	PRON
ispiv-131	36	22	may	may	AUX
ispiv-131	36	23	operate	operate	VERB
ispiv-131	36	24	on	on	ADP
ispiv-131	36	25	a	a	DET
ispiv-131	36	26	wide	wide	ADJ
ispiv-131	36	27	range	range	NOUN
ispiv-131	36	28	of	of	ADP
ispiv-131	36	29	particle	particle	NOUN
ispiv-131	36	30	densities	density	NOUN
ispiv-131	36	31	,	,	PUNCT
ispiv-131	36	32	for	for	ADP
ispiv-131	36	33	which	which	PRON
ispiv-131	36	34	the	the	DET
ispiv-131	36	35	importance	importance	NOUN
ispiv-131	36	36	of	of	ADP
ispiv-131	36	37	the	the	DET
ispiv-131	36	38	features	feature	NOUN
ispiv-131	36	39	at	at	ADP
ispiv-131	36	40	various	various	ADJ
ispiv-131	36	41	levels	level	NOUN
ispiv-131	36	42	may	may	AUX
ispiv-131	36	43	vary	vary	VERB
ispiv-131	36	44	within	within	ADP
ispiv-131	36	45	the	the	DET
ispiv-131	36	46	same	same	ADJ
ispiv-131	36	47	training	training	NOUN
ispiv-131	36	48	dataset	dataset	NOUN
ispiv-131	36	49	.	.	PUNCT
ispiv-131	37	1	finally	finally	ADV
ispiv-131	37	2	,	,	PUNCT
ispiv-131	37	3	we	we	PRON
ispiv-131	37	4	studied	study	VERB
ispiv-131	37	5	layouts	layout	NOUN
ispiv-131	37	6	with	with	ADP
ispiv-131	37	7	a	a	DET
ispiv-131	37	8	dropout	dropout	NOUN
ispiv-131	37	9	layer	layer	NOUN
ispiv-131	37	10	positioned	position	VERB
ispiv-131	37	11	after	after	ADP
ispiv-131	37	12	each	each	DET
ispiv-131	37	13	flow	flow	NOUN
ispiv-131	37	14	inference	inference	NOUN
ispiv-131	37	15	module	module	NOUN
ispiv-131	37	16	and	and	CCONJ
ispiv-131	37	17	after	after	ADP
ispiv-131	37	18	all	all	DET
ispiv-131	37	19	modules	module	NOUN
ispiv-131	37	20	,	,	PUNCT
ispiv-131	37	21	achieving	achieve	VERB
ispiv-131	37	22	the	the	DET
ispiv-131	37	23	best	good	ADJ
ispiv-131	37	24	performance	performance	NOUN
ispiv-131	37	25	when	when	SCONJ
ispiv-131	37	26	placing	place	VERB
ispiv-131	37	27	a	a	DET
ispiv-131	37	28	dropout	dropout	NOUN
ispiv-131	37	29	layer	layer	NOUN
ispiv-131	37	30	after	after	ADP
ispiv-131	37	31	each	each	DET
ispiv-131	37	32	matching	matching	NOUN
ispiv-131	37	33	module	module	NOUN
ispiv-131	37	34	for	for	ADP
ispiv-131	37	35	all	all	DET
ispiv-131	37	36	levels	level	NOUN
ispiv-131	37	37	.	.	PUNCT
ispiv-131	38	1	to	to	PART
ispiv-131	38	2	compare	compare	VERB
ispiv-131	38	3	all	all	DET
ispiv-131	38	4	the	the	DET
ispiv-131	38	5	approaches	approach	NOUN
ispiv-131	38	6	described	describe	VERB
ispiv-131	38	7	,	,	PUNCT
ispiv-131	38	8	we	we	PRON
ispiv-131	38	9	trained	train	VERB
ispiv-131	38	10	our	our	PRON
ispiv-131	38	11	modified	modified	ADJ
ispiv-131	38	12	network	network	NOUN
ispiv-131	38	13	on	on	ADP
ispiv-131	38	14	three	three	NUM
ispiv-131	38	15	piv	piv	NOUN
ispiv-131	38	16	-	-	PUNCT
ispiv-131	38	17	specific	specific	ADJ
ispiv-131	38	18	datasets	dataset	NOUN
ispiv-131	38	19	generated	generate	VERB
ispiv-131	38	20	through	through	ADP
ispiv-131	38	21	numerical	numerical	PROPN
ispiv-131	38	22	simulation	simulation	PROPN
ispiv-131	38	23	(	(	PUNCT
ispiv-131	38	24	cai	cai	X
ispiv-131	38	25	et	et	PROPN
ispiv-131	38	26	al	al	PROPN
ispiv-131	38	27	.	.	PROPN
ispiv-131	38	28	,	,	PUNCT
ispiv-131	38	29	2019	2019	NUM
ispiv-131	38	30	)	)	PUNCT
ispiv-131	38	31	.	.	PUNCT
ispiv-131	39	1	results	result	NOUN
ispiv-131	39	2	in	in	ADP
ispiv-131	39	3	fig	fig	NOUN
ispiv-131	39	4	.	.	PUNCT
ispiv-131	40	1	1(b	1(b	X
ispiv-131	40	2	)	)	PUNCT
ispiv-131	40	3	show	show	VERB
ispiv-131	40	4	consistent	consistent	ADJ
ispiv-131	40	5	performance	performance	NOUN
ispiv-131	40	6	improvements	improvement	NOUN
ispiv-131	40	7	of	of	ADP
ispiv-131	40	8	the	the	DET
ispiv-131	40	9	proposed	propose	VERB
ispiv-131	40	10	network	network	NOUN
ispiv-131	40	11	leveraging	leverage	VERB
ispiv-131	40	12	dropouts	dropout	NOUN
ispiv-131	40	13	(	(	PUNCT
ispiv-131	40	14	p1	p1	PROPN
ispiv-131	40	15	)	)	PUNCT
ispiv-131	40	16	which	which	PRON
ispiv-131	40	17	contained	contain	VERB
ispiv-131	40	18	small	small	ADJ
ispiv-131	40	19	uncertainty	uncertainty	NOUN
ispiv-131	40	20	(	(	PUNCT
ispiv-131	40	21	u1	u1	NOUN
ispiv-131	40	22	)	)	PUNCT
ispiv-131	40	23	for	for	ADP
ispiv-131	40	24	all	all	DET
ispiv-131	40	25	the	the	DET
ispiv-131	40	26	datasets	dataset	NOUN
ispiv-131	40	27	considered	consider	VERB
ispiv-131	40	28	.	.	PUNCT
ispiv-131	41	1	we	we	PRON
ispiv-131	41	2	also	also	ADV
ispiv-131	41	3	determined	determine	VERB
ispiv-131	41	4	optimal	optimal	ADJ
ispiv-131	41	5	weighted	weight	VERB
ispiv-131	41	6	losses	loss	NOUN
ispiv-131	41	7	from	from	ADP
ispiv-131	41	8	various	various	ADJ
ispiv-131	41	9	levels	level	NOUN
ispiv-131	41	10	,	,	PUNCT
ispiv-131	41	11	obtaining	obtain	VERB
ispiv-131	41	12	reduced	reduce	VERB
ispiv-131	41	13	accuracy	accuracy	NOUN
ispiv-131	41	14	(	(	PUNCT
ispiv-131	41	15	p2	p2	PROPN
ispiv-131	41	16	)	)	PUNCT
ispiv-131	41	17	and	and	CCONJ
ispiv-131	41	18	larger	large	ADJ
ispiv-131	41	19	uncertainties	uncertainty	NOUN
ispiv-131	41	20	(	(	PUNCT
ispiv-131	41	21	u2	u2	NOUN
ispiv-131	41	22	)	)	PUNCT
ispiv-131	41	23	,	,	PUNCT
ispiv-131	41	24	confirming	confirm	VERB
ispiv-131	41	25	the	the	DET
ispiv-131	41	26	key	key	ADJ
ispiv-131	41	27	importance	importance	NOUN
ispiv-131	41	28	of	of	ADP
ispiv-131	41	29	high	high	ADJ
ispiv-131	41	30	resolution	resolution	NOUN
ispiv-131	41	31	losses	loss	NOUN
ispiv-131	41	32	and	and	CCONJ
ispiv-131	41	33	providing	provide	VERB
ispiv-131	41	34	grounds	ground	NOUN
ispiv-131	41	35	for	for	ADP
ispiv-131	41	36	designing	design	VERB
ispiv-131	41	37	more	more	ADV
ispiv-131	41	38	efficient	efficient	ADJ
ispiv-131	41	39	network	network	NOUN
ispiv-131	41	40	layouts	layout	NOUN
ispiv-131	41	41	.	.	PUNCT
ispiv-131	42	1	references	reference	NOUN
ispiv-131	42	2	cai	cai	PROPN
ispiv-131	42	3	s	s	PROPN
ispiv-131	42	4	,	,	PUNCT
ispiv-131	42	5	liang	liang	PROPN
ispiv-131	42	6	j	j	PROPN
ispiv-131	42	7	,	,	PUNCT
ispiv-131	42	8	gao	gao	PROPN
ispiv-131	42	9	q	q	PROPN
ispiv-131	42	10	,	,	PUNCT
ispiv-131	42	11	xu	xu	PROPN
ispiv-131	43	1	c	c	X
ispiv-131	43	2	,	,	PUNCT
ispiv-131	43	3	and	and	CCONJ
ispiv-131	43	4	wei	wei	PROPN
ispiv-131	43	5	r	r	PROPN
ispiv-131	43	6	(	(	PUNCT
ispiv-131	43	7	2019	2019	NUM
ispiv-131	43	8	)	)	PUNCT
ispiv-131	43	9	particle	particle	NOUN
ispiv-131	43	10	image	image	NOUN
ispiv-131	43	11	velocimetry	velocimetry	NOUN
ispiv-131	43	12	based	base	VERB
ispiv-131	43	13	on	on	ADP
ispiv-131	43	14	a	a	DET
ispiv-131	43	15	deep	deep	ADJ
ispiv-131	43	16	learning	learning	NOUN
ispiv-131	43	17	motion	motion	NOUN
ispiv-131	43	18	estimator	estimator	NOUN
ispiv-131	43	19	.	.	PUNCT
ispiv-131	44	1	ieee	ieee	NOUN
ispiv-131	44	2	transactions	transaction	NOUN
ispiv-131	44	3	on	on	ADP
ispiv-131	44	4	instrumentation	instrumentation	NOUN
ispiv-131	44	5	and	and	CCONJ
ispiv-131	44	6	measurement	measurement	NOUN
ispiv-131	44	7	69:3538–3554	69:3538–3554	NUM
ispiv-131	44	8	horn	horn	VERB
ispiv-131	44	9	bk	bk	NOUN
ispiv-131	44	10	and	and	CCONJ
ispiv-131	44	11	schunck	schunck	ADJ
ispiv-131	44	12	bg	bg	PROPN
ispiv-131	44	13	(	(	PUNCT
ispiv-131	44	14	1981	1981	NUM
ispiv-131	44	15	)	)	PUNCT
ispiv-131	44	16	determining	determine	VERB
ispiv-131	44	17	optical	optical	ADJ
ispiv-131	44	18	flow	flow	NOUN
ispiv-131	44	19	.	.	PUNCT
ispiv-131	45	1	in	in	ADP
ispiv-131	45	2	techniques	technique	NOUN
ispiv-131	45	3	and	and	CCONJ
ispiv-131	45	4	applications	application	NOUN
ispiv-131	45	5	of	of	ADP
ispiv-131	45	6	image	image	NOUN
ispiv-131	45	7	understanding	understanding	NOUN
ispiv-131	45	8	.	.	PUNCT
ispiv-131	46	1	volume	volume	NOUN
ispiv-131	46	2	281	281	NUM
ispiv-131	46	3	.	.	PUNCT
ispiv-131	47	1	pages	page	NOUN
ispiv-131	47	2	319–331	319–331	NUM
ispiv-131	47	3	.	.	PUNCT
ispiv-131	48	1	international	international	ADJ
ispiv-131	48	2	society	society	NOUN
ispiv-131	48	3	for	for	ADP
ispiv-131	48	4	optics	optic	NOUN
ispiv-131	48	5	and	and	CCONJ
ispiv-131	48	6	photonics	photonics	PROPN
ispiv-131	48	7	hui	hui	PROPN
ispiv-131	48	8	tw	tw	PROPN
ispiv-131	48	9	,	,	PUNCT
ispiv-131	48	10	tang	tang	PROPN
ispiv-131	48	11	x	x	X
ispiv-131	48	12	,	,	PUNCT
ispiv-131	48	13	and	and	CCONJ
ispiv-131	48	14	loy	loy	PROPN
ispiv-131	48	15	c	c	PROPN
ispiv-131	48	16	(	(	PUNCT
ispiv-131	48	17	2018	2018	NUM
ispiv-131	48	18	)	)	PUNCT
ispiv-131	48	19	liteflownet	liteflownet	NOUN
ispiv-131	48	20	:	:	PUNCT
ispiv-131	48	21	a	a	DET
ispiv-131	48	22	lightweight	lightweight	ADJ
ispiv-131	48	23	convolutional	convolutional	ADJ
ispiv-131	48	24	neural	neural	ADJ
ispiv-131	48	25	network	network	NOUN
ispiv-131	48	26	for	for	ADP
ispiv-131	48	27	optical	optical	ADJ
ispiv-131	48	28	flow	flow	NOUN
ispiv-131	48	29	estimation	estimation	NOUN
ispiv-131	48	30	.	.	PUNCT
ispiv-131	49	1	in	in	ADP
ispiv-131	49	2	proceedings	proceeding	NOUN
ispiv-131	49	3	of	of	ADP
ispiv-131	49	4	ieee	ieee	NOUN
ispiv-131	49	5	conference	conference	NOUN
ispiv-131	49	6	on	on	ADP
ispiv-131	49	7	computer	computer	NOUN
ispiv-131	49	8	vision	vision	NOUN
ispiv-131	49	9	and	and	CCONJ
ispiv-131	49	10	pattern	pattern	NOUN
ispiv-131	49	11	recognition	recognition	NOUN
ispiv-131	49	12	(	(	PUNCT
ispiv-131	49	13	cvpr	cvpr	NOUN
ispiv-131	49	14	)	)	PUNCT
ispiv-131	49	15	.	.	PUNCT
ispiv-131	50	1	pages	page	NOUN
ispiv-131	50	2	8981–8989	8981–8989	PROPN
ispiv-131	50	3	hui	hui	PROPN
ispiv-131	50	4	tw	tw	PROPN
ispiv-131	50	5	,	,	PUNCT
ispiv-131	50	6	tang	tang	PROPN
ispiv-131	50	7	x	x	X
ispiv-131	50	8	,	,	PUNCT
ispiv-131	50	9	and	and	CCONJ
ispiv-131	50	10	loy	loy	PROPN
ispiv-131	50	11	c	c	PROPN
ispiv-131	50	12	(	(	PUNCT
ispiv-131	50	13	2020	2020	NUM
ispiv-131	50	14	)	)	PUNCT
ispiv-131	50	15	a	a	DET
ispiv-131	50	16	lightweight	lightweight	ADJ
ispiv-131	50	17	optical	optical	ADJ
ispiv-131	50	18	flow	flow	NOUN
ispiv-131	50	19	cnn	cnn	PROPN
ispiv-131	50	20	revisiting	revisit	VERB
ispiv-131	50	21	data	datum	NOUN
ispiv-131	50	22	fidelity	fidelity	NOUN
ispiv-131	50	23	and	and	CCONJ
ispiv-131	50	24	regularization	regularization	NOUN
ispiv-131	50	25	introduction	introduction	NOUN
ispiv-131	50	26	methods	method	NOUN
ispiv-131	50	27	results	result	VERB