Datasets:

Video-Index
/

Video-Index-v1-1

item_id stringlengths 8 21	benchmark stringlengths 4 16	capability_group stringclasses 4 values	capability_group_label stringclasses 4 values	fine_category stringclasses 17 values	question stringlengths 26 629	options listlengths 2 8	answer stringclasses 7 values	answer_idx int64 0 6	chance float64 0.13 0.5	video stringlengths 75 75	video_id stringlengths 64 64	duration_s float64 1.91 9.4k	width int64 280 4.1k ⌀	height int64 240 2.3k ⌀	fps stringclasses 25 values	audio dict	source_video stringlengths 25 140	video_v1_0 stringlengths 75 75	license stringclasses 9 values	answer_v1_0 stringclasses 2 values
AoTBench_4027	AoTBench	perception	Perception	perception_object_misidentify	Which caption best describes this video?	[ "A young beautiful woman with headphones closes her eyes, and holds her cheeks to enjoy the music, at the end, she dropped her hands down.", "A beautiful girl lays down on the yoga mat cheerfully after workouting at home." ]	B	1	0.5	videos/dcc3546a5d0875b6b6f2c5f54730f728247b7685a5b6dad8955d66942a6f7bc3.mp4	dcc3546a5d0875b6b6f2c5f54730f728247b7685a5b6dad8955d66942a6f7bc3	15.4	596	336	25/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1085270597-young-beautiful-asian-woman-put-on-headphone_reverse.mp4	videos/dcc3546a5d0875b6b6f2c5f54730f728247b7685a5b6dad8955d66942a6f7bc3.mp4	unknown	null
AoTBench_5903	AoTBench	perception	Perception	perception_fine_grained_action	Which caption best describes this video?	[ "Wonderful hilly terrain with high natural mountains and dense green forest top view raising over winding asphalt road with moving cars at sunset or sunrise.", "Two cars are backing up over a winding asphalt road with wonderful hilly terrain with high natural mountains and dense green forest top view raising" ]	B	1	0.5	videos/d6b7428fe6aaa32fa25fc9872d8b6d50ba9d7576f6113745551656de26af7333.mp4	d6b7428fe6aaa32fa25fc9872d8b6d50ba9d7576f6113745551656de26af7333	18.285	596	336	30000/1001	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1018728370-aerial-shot-taking-off-over-wonderful-hilly_reverse.mp4	videos/d6b7428fe6aaa32fa25fc9872d8b6d50ba9d7576f6113745551656de26af7333.mp4	unknown	null
AoTBench_4425	AoTBench	perception	Perception	perception_fine_grained_action	Which caption best describes this video?	[ "A woman is skillfully wrapping a piece of yarn around two sticks.", "A piece of yarn was gradually pulled out from two yarn sticks by a nimble girl." ]	B	1	0.5	videos/bee277af78ee0bcfc65004e9f4941a2e59d2f7080c79a416ecb641d8c5bd2849.mp4	bee277af78ee0bcfc65004e9f4941a2e59d2f7080c79a416ecb641d8c5bd2849	20.12	596	336	25/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1058945132-woman-s-hands-knitting-craft-needles-red-wool_reverse.mp4	videos/bee277af78ee0bcfc65004e9f4941a2e59d2f7080c79a416ecb641d8c5bd2849.mp4	unknown	null
VITATECS_8206	VITATECS	perception	Perception	perception_fine_grained_action	Which caption correctly describes what happens in the video?	[ "certain species of fish crawling around on the ocean floor", "certain species of fish swimming around near the ocean floor" ]	A	0	0.5	videos/850b48b37b090787da02f722b4d8fae66196fb2aaaca479b543ccf1c4cf315dd.mp4	850b48b37b090787da02f722b4d8fae66196fb2aaaca479b543ccf1c4cf315dd	10.01	320	240	30000/1001	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	sherryxzh/AoTBench::videos.zip::videos/vitatecs/video7530.mp4	videos/850b48b37b090787da02f722b4d8fae66196fb2aaaca479b543ccf1c4cf315dd.mp4	CC-BY-4.0	null
V2P-Bench_988	V2P-Bench	perception	Perception	perception_localization	What are the planets that the man marked with a red dot research?	[ "Mars and Jupiter.", "Venus and Neptune.", "Mars and Neptune.", "Jupiter and Neptune." ]	B	1	0.25	videos/a1ad8b7d5781e071abe4102786f98ccd63c04be9933dfe4a076ed2aa7f6d750b.mp4	a1ad8b7d5781e071abe4102786f98ccd63c04be9933dfe4a076ed2aa7f6d750b	2,766.82	1,280	720	2997/100	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	gaotiexinqu/V2P-Bench::videos/Video-MME_xk.zip::Video-MME_xk/rD5oDjk3IOU.mp4	videos/a1ad8b7d5781e071abe4102786f98ccd63c04be9933dfe4a076ed2aa7f6d750b.mp4	CC-BY-NC-4.0	null
ALLVB_2121	ALLVB	perception	Perception	perception_attribute	In the dark, swampy environment, a woman is seen tending to a wounded person and later crawling through the muddy terrain while holding a gun. The scene is filled with dense vegetation, water, and dim lighting. What is the color of the woman's shirt in the scene?	[ "Blue", "Red", "Black", "Green", "Purple" ]	E	4	0.2	videos/7b46602803092cb7c2bb0d8e9d836544b91a1a95480a8b029787430997726e9e.mp4	7b46602803092cb7c2bb0d8e9d836544b91a1a95480a8b029787430997726e9e	5,252.08	1,280	534	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Crawl (2019)/Crawl (2019).mp4	videos/7b46602803092cb7c2bb0d8e9d836544b91a1a95480a8b029787430997726e9e.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_7790	S-EMBER	perception	Perception	perception_comparison	How does the shade of these green pants compare to the green pants I looked at earlier?	[ "These pants are a lighter, more olive shade compared to the darker green pants you looked at earlier.", "These pants are noticeably darker and more muted, whereas the pants you saw earlier were lighter and brighter.", "These pants are a lighter, pastel green, while the earlier pair was a noticeably darker, dee...	D	3	0.2	videos/f4eb7be9d552eedd74a88056791638265d916e8bbdbe2eae63a157d9657b4751.mp4	f4eb7be9d552eedd74a88056791638265d916e8bbdbe2eae63a157d9657b4751	300.167	720	966	12/1	null	facebook/S-EMBER::::videos/1266650815111130_start_0.0_end_300.12.mp4	videos/f4eb7be9d552eedd74a88056791638265d916e8bbdbe2eae63a157d9657b4751.mp4	CC-BY-NC-4.0	null
TOC-Bench_862	TOC-Bench	perception	Perception	perception_hallucination	Does eggs ever get fully hidden in the video?	[ "eggs never gets fully hidden", "eggs does gets fully hidden" ]	B	1	0.5	videos/6c23b5ed384eb06d60b1189bc7a73b83afe5e537a5653c5c8df78e40abcc3aff.mp4	6c23b5ed384eb06d60b1189bc7a73b83afe5e537a5653c5c8df78e40abcc3aff	26.122	1,920	1,080	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 1 }	anonymous-video-benchmark/toc_bench::::videos/perception_test_video_1025.mp4	videos/6c23b5ed384eb06d60b1189bc7a73b83afe5e537a5653c5c8df78e40abcc3aff.mp4	custom	null
S-EMBER_346	S-EMBER	perception	Perception	perception_object_counting	After coming to a stop, how many yellow taxis did I see before I crossed the street?	[ "You saw 6 yellow taxis before crossing.", "You saw 3 yellow taxis before crossing.", "You saw 5 yellow taxis before crossing.", "You saw 2 yellow taxis before crossing.", "You saw 8 yellow taxis before crossing." ]	E	4	0.2	videos/9236e84d67124084e51188834a5bfee561f07014f5c2015ff83cf6f67497c425.mp4	9236e84d67124084e51188834a5bfee561f07014f5c2015ff83cf6f67497c425	600	720	960	12/1	null	facebook/S-EMBER::::videos/9990797240986613_start_0.0_end_599.986.mp4	videos/9236e84d67124084e51188834a5bfee561f07014f5c2015ff83cf6f67497c425.mp4	CC-BY-NC-4.0	null
AoTBench_4309	AoTBench	perception	Perception	perception_object_misidentify	Which caption best describes this video?	[ "An old lady with gray hair and a blue mask is flipping through a book.", "A book is being read upside down by an old lady with a blue mask on her hair and a red sweater." ]	B	1	0.5	videos/1fcb463916ff85d3474d4041757c0b806baca95ba31fffbcacc05e72f62860dc.mp4	1fcb463916ff85d3474d4041757c0b806baca95ba31fffbcacc05e72f62860dc	18.36	596	336	25/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1053321791-close-senior-caucasian-woman-protective-mask-on_reverse.mp4	videos/1fcb463916ff85d3474d4041757c0b806baca95ba31fffbcacc05e72f62860dc.mp4	unknown	null
ViMUL-Bench_4920	ViMUL-Bench	perception	Perception	perception_comparison	第三のステッカーセットは他の二つと何が違うのですか？	[ "3番目のシールセットは動物柄です。", "三番目のステッカーセットは植物のパターンです。", "3番目のステッカーセットは安価です。", "三番目のステッカーセットには色がありません。" ]	D	3	0.25	videos/d075591bcaef6db39f41a8d6b30c6567bbfbabdbc3f69daf6ed4d2e0b992acf7.mp4	d075591bcaef6db39f41a8d6b30c6567bbfbabdbc3f69daf6ed4d2e0b992acf7	2,180.725	640	360	25/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	MBZUAI/ViMUL-Bench::videos.zip::vid_4004.mp4	videos/d075591bcaef6db39f41a8d6b30c6567bbfbabdbc3f69daf6ed4d2e0b992acf7.mp4	CC-BY-SA-4.0	null
K9-Bench_2956	K9-Bench	perception	Perception	perception_fine_grained_action	Trace the interaction loop that begins with the puppy exhibiting dominant mounting behavior towards the adult dog in the backyard, and how the adult dog's subsequent actions attempt to alter this dynamic.	[ "The puppy mounts with curved tail wagging. The adult ducks head, turns away, sits abruptly to submit.", "The puppy mounts with nudging and nipping. The adult twists, whimpers, lies down with head turned away to submit.", "The puppy mounts with pounce, head high. The adult shifts weight, moves beneath, freezes ...	E	4	0.2	videos/731ea791d75056f405c65196e4df681cbe602a736b5d8435b80acafd3406026d.mp4	731ea791d75056f405c65196e4df681cbe602a736b5d8435b80acafd3406026d	584.061	null	null	null	{ "codec": "opus", "sample_rate": "48000", "channels": 2 }	yt::K9-Bench::::5MV8T70xiGM	videos/774b1c9ccb18d5187b2674c72feaa1b76ca35c1071151142a24798134ca5ef87.mp4	CC-BY-NC-4.0	null
VideoAds_128	VideoAds	perception	Perception	perception_object_misidentify	What animals appear in the video?	[ "The video features a bear.", "The stuffed animals in the video include a lion and a panda.", "The video shows the fox", "The video showcases a panda among other stuffed animals." ]	C	2	0.25	videos/1ae07a1f7e19db50e9d4fec541faade5723d1a16e01e3f0de516be2112a322fb.mp4	1ae07a1f7e19db50e9d4fec541faade5723d1a16e01e3f0de516be2112a322fb	60.04	1,920	1,080	25/1	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	Zheyuan14/VideoAds::videoads.zip::videoads/youtube_videos/ads_3P3Pjti08wo.mp4	videos/1ae07a1f7e19db50e9d4fec541faade5723d1a16e01e3f0de516be2112a322fb.mp4	custom	null
VF-Eval_3756	VF-Eval	perception	Perception	perception_attribute	What issue can be observed with the firewood?	[ "The firewood has started to rot and decay", "The firewood has been poorly seasoned", "The firewood is damp and unsuitable for burning", "The grain of the firewood is constantly twisting." ]	D	3	0.25	videos/30218867f5a69842813eba904b22b883b1b06c1ada8753e3da2d6fdc3a8226ba.mp4	30218867f5a69842813eba904b22b883b1b06c1ada8753e3da2d6fdc3a8226ba	7	1,280	720	24/1	null	songtingyu/vf-eval::videos.zip::videos/data/video-data/pika/data/pika/data/pika_319_.mp4	videos/30218867f5a69842813eba904b22b883b1b06c1ada8753e3da2d6fdc3a8226ba.mp4	MIT	null
TOC-Bench_57	TOC-Bench	perception	Perception	perception_hallucination	Does metallic containers ever disappear for good in the video?	[ "metallic containers never disappears for good", "metallic containers does disappear for good" ]	B	1	0.5	videos/90267cfc4a03b057c67d4e05736127cf1225926bb72e927728a11484c3040934.mp4	90267cfc4a03b057c67d4e05736127cf1225926bb72e927728a11484c3040934	34.342	480	268	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	anonymous-video-benchmark/toc_bench::::videos/charades_2QWGI.mp4	videos/90267cfc4a03b057c67d4e05736127cf1225926bb72e927728a11484c3040934.mp4	custom	null
ALLVB_12052	ALLVB	perception	Perception	perception_fine_grained_action	What variations of the action of waiting are depicted in the script?	[ "Waiting to wash hands and waiting to drink water", "Waiting to enter a room and waiting to leave a room", "Waiting to sit down and waiting to stand up", "Waiting to speak and waiting to listen", "Waiting to eat and waiting to sleep" ]	A	0	0.2	videos/25e45264c4da3ac6231ab0ca596264c7fc9054607c6deab126fad86bf3f4f9b3.mp4	25e45264c4da3ac6231ab0ca596264c7fc9054607c6deab126fad86bf3f4f9b3	5,618.656	1,280	682	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Eighth Grade (2018)/Eighth Grade (2018).mp4	videos/25e45264c4da3ac6231ab0ca596264c7fc9054607c6deab126fad86bf3f4f9b3.mp4	CC-BY-NC-SA-4.0	null
FAVOR-Bench_2183	FAVOR-Bench	perception	Perception	perception_fine_grained_action	What is the accompanying physical movement characteristic of the man wearing a light-colored tie while speaking?	[ "Rapidly extending and retracting his arms", "Continuously adjusting the position of the tie knot with his right hand", "Keeping his left hand stationary on the edge of the dining table", "Suddenly leaning his upper body forward more than 15 degrees", "Continuously tapping the cover of the documents with hi...	A	0	0.2	videos/27ed04966baba926092ec93a956615690e7f68eba31c947b08fef958e2f4be01.mp4	27ed04966baba926092ec93a956615690e7f68eba31c947b08fef958e2f4be01	5.04	1,280	654	25/1	null	FAVOR-Bench/FAVOR::::videos/FAVOR-Bench/2_05_001769.mp4	videos/27ed04966baba926092ec93a956615690e7f68eba31c947b08fef958e2f4be01.mp4	CC-BY-NC-SA-4.0	null
Video-TT_1384	Video-TT	perception	Perception	perception_hallucination	What does the video express?	[ "It humorously compares romantic preferences using cats.", "It shows cats mimicking human expressions.", "It uses special effects to make a cat appear to sing.", "It contrasts idealized preferences and reality." ]	C	2	0.25	videos/39b7525fe36cd497776999706b9a827acfcd3e1a3b2f4fa027d295a692a56a7a.mp4	39b7525fe36cd497776999706b9a827acfcd3e1a3b2f4fa027d295a692a56a7a	7.895	1,080	1,920	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	lmms-eval/video-tt::Benchmark-AllVideos-HQ-encoded_part1.zip::Benchmark-AllVideos-HQ-encoded/42UcNjI_YlE.mp4	videos/39b7525fe36cd497776999706b9a827acfcd3e1a3b2f4fa027d295a692a56a7a.mp4	MIT	null
Video-TT_2289	Video-TT	perception	Perception	perception_object_misidentify	What does the second image taken with the Sony 24-70mm f/2.8 lens show?	[ "It's impossible to determine the exact second image.", "Two motorcyclists and a green vehicle on a winding road", "Three motorcycles in the front and a car behind", "A green Toyota vehicle on a road with greenery" ]	C	2	0.25	videos/7c85a08be66e105b88cdf2d9500181c8737143e7268f6fad39363b5978a2b4d2.mp4	7c85a08be66e105b88cdf2d9500181c8737143e7268f6fad39363b5978a2b4d2	11.563	1,080	1,920	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	lmms-eval/video-tt::Benchmark-AllVideos-HQ-encoded_part3.zip::Benchmark-AllVideos-HQ-encoded/4LS2TBap9nU.mp4	videos/7c85a08be66e105b88cdf2d9500181c8737143e7268f6fad39363b5978a2b4d2.mp4	MIT	null
AoTBench_5351	AoTBench	perception	Perception	perception_fine_grained_action	Which caption best describes this video?	[ "Large paper sheets in different colors were flipped over one after another slowly by somebody.", "Different colored sheets of paper were paved slowly one after the other." ]	B	1	0.5	videos/413bd50cc5fc0f8de223dfc536a280cce6f0297681775f6b8e9218b50cf5d6e5.mp4	413bd50cc5fc0f8de223dfc536a280cce6f0297681775f6b8e9218b50cf5d6e5	16	596	336	30/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1056712910-flipping-colorful-pages-4k-3d-animation-being_reverse.mp4	videos/413bd50cc5fc0f8de223dfc536a280cce6f0297681775f6b8e9218b50cf5d6e5.mp4	unknown	null
S-EMBER_6606	S-EMBER	perception	Perception	perception_fine_grained_action	What did I do with the second blank white card that I was holding earlier?	[ "You set it down on the coffee table in front of the couch.", "You held it in your hand while writing on another card with a marker.", "You put it back down on the table with the rest of the unused cards.", "You placed it on the table and picked it up to write on it.", "You handed it to the person sitting a...	E	4	0.2	videos/83f280a3bcc033d789c0bcea75cf0186a35706a54ca31897d7114fd65c6e9789.mp4	83f280a3bcc033d789c0bcea75cf0186a35706a54ca31897d7114fd65c6e9789	1,200.25	720	958	12/1	null	facebook/S-EMBER::::videos/1054177859931507_start_0.0_end_1200.308.mp4	videos/83f280a3bcc033d789c0bcea75cf0186a35706a54ca31897d7114fd65c6e9789.mp4	CC-BY-NC-4.0	null
TOC-Bench_1401	TOC-Bench	perception	Perception	perception_hallucination	Does white cloth ever disappear for good in the video?	[ "white cloth never disappears for good", "white cloth does disappear for good" ]	B	1	0.5	videos/de317cff2a68a05ec3bc791848ba699752c0c561b0547a314e67cf4733eed776.mp4	de317cff2a68a05ec3bc791848ba699752c0c561b0547a314e67cf4733eed776	31.741	480	270	16641/1000	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	lmms-eval/charades_sta::Charades_v1_480_part_1.zip::Charades_v1_480/GNPSK.mp4	videos/de317cff2a68a05ec3bc791848ba699752c0c561b0547a314e67cf4733eed776.mp4	custom	null
K9-Bench_4309	K9-Bench	perception	Perception	perception_fine_grained_action	What specific behaviors does the dog use to communicate desire for treats in the kitchen and how do these demonstrate understanding of the routine?	[ "Sits, rises, nudges other dog, whines, stands hind legs on human's leg, wags tail, stares.", "Observes, mirrors other dog, growls, stands hind legs on cupboard, wags tail energetically, fixates on human.", "Waits, aligns with other dog, yips, stands hind legs on human's arm, wags tail excitedly, makes eye cont...	D	3	0.2	videos/dc380aef850435e00d70216ad580cc6372930801fcebabc5a113026d903b0823.mp4	dc380aef850435e00d70216ad580cc6372930801fcebabc5a113026d903b0823	272.761	null	null	null	{ "codec": "opus", "sample_rate": "48000", "channels": 2 }	yt::K9-Bench::::9kt4SefXBrU	videos/04d4480b66d590f48e74ad8d28517f334696c52054b637fd661a1deff2204ca4.mp4	CC-BY-NC-4.0	null
ALLVB_14913	ALLVB	perception	Perception	perception_object_misidentify	What type of vehicle does Merlin use to travel to the high promontory?	[ "A horse", "A chariot", "A mule", "A carriage", "A dragon" ]	C	2	0.2	videos/1469da3e525dea9fd72680686b3613229344593f7ac830cf23933b1d38879099.mp4	1469da3e525dea9fd72680686b3613229344593f7ac830cf23933b1d38879099	8,447.147	1,280	720	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Excalibur (1981)/Excalibur (1981).mp4	videos/1469da3e525dea9fd72680686b3613229344593f7ac830cf23933b1d38879099.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_2539	S-EMBER	perception	Perception	perception_comparison	How do these two LEGO figures compare to the last two I put on the winter scene?	[ "These two are brightly colored without winter gear, while the last two wore heavy coats and were posed for sledding.", "Both pairs of figures feature an elf character, but the second figure in each of the pairs is entirely different.", "These two are the same size as the previous two, but one features a gold-c...	E	4	0.2	videos/4d78241eeca838fc2a8bae06a0372afa963055d1c9cfd2acc2df9f24eac1dfb1.mp4	4d78241eeca838fc2a8bae06a0372afa963055d1c9cfd2acc2df9f24eac1dfb1	414.25	720	962	12/1	null	facebook/S-EMBER::::videos/1269236014904502_start_0.0_end_414.218.mp4	videos/4d78241eeca838fc2a8bae06a0372afa963055d1c9cfd2acc2df9f24eac1dfb1.mp4	CC-BY-NC-4.0	null
ALLVB_12953	ALLVB	perception	Perception	ocr_text	How often does the name "Mayfield" appear in the scenes set in Mayfield?	[ "Once", "Twice", "Three times", "Four times", "Five times" ]	E	4	0.2	videos/f5890587406a83aa50bba239a78da963258b52343ffc6a25fb75cd8e2b70fc97.mp4	f5890587406a83aa50bba239a78da963258b52343ffc6a25fb75cd8e2b70fc97	7,265.167	1,280	534	24/1	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/The Sisters Brothers (2018)/The Sisters Brothers (2018).mp4	videos/f5890587406a83aa50bba239a78da963258b52343ffc6a25fb75cd8e2b70fc97.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_1448	S-EMBER	perception	Perception	perception_object_counting	How many white plates with the blue design did I take out of the dishwasher?	[ "Zero.", "Four.", "Six.", "Three.", "Ten." ]	E	4	0.2	videos/2b4075f9e0645206857d5061e8bc5f3d18555e9e35781badfef9c70dae8d9173.mp4	2b4075f9e0645206857d5061e8bc5f3d18555e9e35781badfef9c70dae8d9173	600	720	966	12/1	null	facebook/S-EMBER::::videos/1218799153211769_start_0.0_end_599.992.mp4	videos/2b4075f9e0645206857d5061e8bc5f3d18555e9e35781badfef9c70dae8d9173.mp4	CC-BY-NC-4.0	null
S-EMBER_2431	S-EMBER	perception	Perception	perception_comparison	How does this pair of shorts differ from the ones I just saw on the floor?	[ "This pair of shorts is white and clean, whereas the ones on the floor were dark blue.", "This pair of shorts is embellished with rhinestones, whereas the ones on the floor were plain.", "This pair of shorts is olive-green on a hanger, whereas the ones on the floor were blue denim.", "This pair of shorts is l...	E	4	0.2	videos/b69ffc04dcb2de08470e1c79fdd914d7574a9d45ed90e40fdf286a4ec8585810.mp4	b69ffc04dcb2de08470e1c79fdd914d7574a9d45ed90e40fdf286a4ec8585810	1,200.333	720	954	12/1	null	facebook/S-EMBER::::videos/1217617540090524_start_0.0_end_1200.322.mp4	videos/b69ffc04dcb2de08470e1c79fdd914d7574a9d45ed90e40fdf286a4ec8585810.mp4	CC-BY-NC-4.0	null
VideoOdyssey_1535	VideoOdyssey	perception	Perception	perception_attribute	What is the hair color of the sixth player who appears for the United States team in this match?	[ "Yellow", "Black", "Platinum blond", "Light brown" ]	A	0	0.25	videos/710cc28c528d004039731f5990d84250d9ed823ad9889cc3389f86b84553bbc2.mp4	710cc28c528d004039731f5990d84250d9ed823ad9889cc3389f86b84553bbc2	9,400.018	1,280	720	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	maifoundations/VideoOdyssey::::videos/d51lKLec2Gg.mp4	videos/710cc28c528d004039731f5990d84250d9ed823ad9889cc3389f86b84553bbc2.mp4	CC-BY-NC-SA-4.0	null
TemporalBench_13536	TemporalBench	perception	Perception	perception_object_misidentify	Which caption best describes this video?	[ "A person outside near a grill. They use their right hand to gently place 5 tubular looking burgers right on the grill. They use their right hand to hold a metal fork that is used to turn and flip the meat. The meat is moved and as it continues to cook, cheese is melting out of it. The person squirts yellow mustar...	B	1	0.5	videos/04d64a7e9be21f39cc1d346c7feb58af1976b73c156aea02c153816f1656034a.mp4	04d64a7e9be21f39cc1d346c7feb58af1976b73c156aea02c153816f1656034a	31	1,280	720	30/1	null	microsoft/TemporalBench::long_video_COIN.zip::long_video/COIN/Cu1QhB1Ma_0_start_30.0_end_61.0.mp4	videos/04d64a7e9be21f39cc1d346c7feb58af1976b73c156aea02c153816f1656034a.mp4		null
VANE-Bench_252	VANE-Bench	perception	Perception	perception_hallucination	What is the major inconsistency observed in the video?	[ "The couple's faces are highly deformed and distorted", "The cars are floating in the air", "The rain is falling upwards", "The street is dry despite the rain" ]	A	0	0.25	videos/688abc442d23eca3aadbbd2e01c49c3a92bea76058ad4d8bc44cfdae137402f6.mp4	688abc442d23eca3aadbbd2e01c49c3a92bea76058ad4d8bc44cfdae137402f6	10	1,408	768	2/1	null	local::VANE-Bench::::local copy	videos/688abc442d23eca3aadbbd2e01c49c3a92bea76058ad4d8bc44cfdae137402f6.mp4	CC-BY-NC-SA-4.0	null
VF-Eval_2827	VF-Eval	perception	Perception	perception_hallucination	Please review the video and check for any quality problems. Quality issues may include low resolution, blurriness, or distortion.	[ "The size of the item in the girl's hand appears disproportionate.", "The outline of the item in the girl's hand appears blurry.", "The color of the item in the girl's hand is inconsistent.", "The lighting on the item in the girl's hand causes unusual shadows." ]	C	2	0.25	videos/b9e5e4866d290b585b81bba7756275aad9f09b0d6e51f5ed1ba0f99ddba6a5e3.mp4	b9e5e4866d290b585b81bba7756275aad9f09b0d6e51f5ed1ba0f99ddba6a5e3	7	1,280	720	24/1	null	songtingyu/vf-eval::videos.zip::videos/data/video-data/pika/data/pika/data/pika_206_.mp4	videos/b9e5e4866d290b585b81bba7756275aad9f09b0d6e51f5ed1ba0f99ddba6a5e3.mp4	MIT	null
VidPair-Halluc_6170	VidPair-Halluc	perception	Perception	perception_fine_grained_action	Which description best matches segment 1 of this video? A. The man stands at the grill, ready to turn the sausages. B. The man stands at the grill, ready to grill the sausages. C. The man stands at the grill, ready to serve the sausages.	[ "{'label': 'A', 'text': 'The man stands at the grill, ready to turn the sausages.'}", "{'label': 'B', 'text': 'The man stands at the grill, ready to grill the sausages.'}", "{'label': 'C', 'text': 'The man stands at the grill, ready to serve the sausages.'}" ]	C	2	0.333333	videos/a881cae8609c81f839fddb7a69aae1d75d80629d1baf5d6364d32e83632172ca.mp4	a881cae8609c81f839fddb7a69aae1d75d80629d1baf5d6364d32e83632172ca	15.188	1,264	720	16/1	null	Jethro37/VidPair-Halluc::::VidPair-Halluc/action_0040/action_0040_2.mp4	videos/a881cae8609c81f839fddb7a69aae1d75d80629d1baf5d6364d32e83632172ca.mp4	custom	null
AoTBench_5899	AoTBench	perception	Perception	perception_object_misidentify	Which caption best describes this video?	[ "The physical rehabilitation process of human legs is accomplished with the help of a track simulator.", "A man does regressive rehabilitation exercises with the help of support equipment." ]	B	1	0.5	videos/3d1da9132f67038b21440ed647cf8caa8bd00af0d84227a2a5bfb817926a0f2b.mp4	3d1da9132f67038b21440ed647cf8caa8bd00af0d84227a2a5bfb817926a0f2b	15.949	596	336	30000/1001	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1018368853-physical-rehabilitation-process-human-legs-accomplished-help_reverse.mp4	videos/3d1da9132f67038b21440ed647cf8caa8bd00af0d84227a2a5bfb817926a0f2b.mp4	unknown	null
TOC-Bench_245	TOC-Bench	perception	Perception	perception_hallucination	Does black pen ever get fully hidden in the video?	[ "black pen never gets fully hidden", "black pen does get fully hidden" ]	B	1	0.5	videos/a4f7ea63f471be4544743fad8b1a1fd98bc6fc4575cca20b1724d11381b36f0e.mp4	a4f7ea63f471be4544743fad8b1a1fd98bc6fc4575cca20b1724d11381b36f0e	29.525	1,280	720	29773/1000	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	lmms-eval/PerceptionTest_Val::videos_chunked_02.zip::videos/video_9105.mp4	videos/a4f7ea63f471be4544743fad8b1a1fd98bc6fc4575cca20b1724d11381b36f0e.mp4	custom	null
AoTBench_4733	AoTBench	temporal	Temporal	temporal_order	Which caption best describes this video?	[ "A man clicks on the oven touch screen to adjust the temperature and time of the oven.", "After clicking the start button, the chef continued to operate on the oven screen." ]	B	1	0.5	videos/27cc654cc2ea451de6ea40a643f8e0ed62996629b0b2f1374532f5ad34aba296.mp4	27cc654cc2ea451de6ea40a643f8e0ed62996629b0b2f1374532f5ad34aba296	22.56	600	316	25/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1068495335-female-finger-regulating-temperature-time-on-touch_reverse.mp4	videos/27cc654cc2ea451de6ea40a643f8e0ed62996629b0b2f1374532f5ad34aba296.mp4	unknown	null
AoTBench_4405	AoTBench	temporal	Temporal	temporal_order	Which caption best describes this video?	[ "The woman in brown wore a white mask, then she pushed the glasses to her forehead and adjusted her hair.", "The woman took off the mask and sunglasses to breathe fresh air and then put the sunglasses on again." ]	B	1	0.5	videos/208ac0199b2a4d7f2eb822640bf77974d72f6410756202682bb9acad5ed4c7bb.mp4	208ac0199b2a4d7f2eb822640bf77974d72f6410756202682bb9acad5ed4c7bb	16.46	596	336	50/1	null	sherryxzh/AoTBench::videos.zip::videos/RTime/clip-1059798743-passenger-puts-on-mask-while-descending-subway_reverse.mp4	videos/208ac0199b2a4d7f2eb822640bf77974d72f6410756202682bb9acad5ed4c7bb.mp4	unknown	null
MMWorld_864	MMWorld	temporal	Temporal	temporal_order	What do the players perform before performing double salto backward tucked?	[ "Before performing double salto backward tucked, the players perform a round-off followed by a back handspring.", "Before performing double salto backward tucked, the players perform a round-off back handspring.", "2 turn in tuck stand on one leg, free leg straight throughout turn", "The players perform a rou...	C	2	0.25	videos/d33e78b90385bcbe57271fe24145622f0f266da80effd09fa503dd66af3d902e.mp4	d33e78b90385bcbe57271fe24145622f0f266da80effd09fa503dd66af3d902e	101	1,920	1,080	25/1	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	MMWorld/MMWorld::::videos/fg/P31Ht3H76ok_E_005884_005984.mp4	videos/d33e78b90385bcbe57271fe24145622f0f266da80effd09fa503dd66af3d902e.mp4		null
HLV-1K_5939	HLV-1K	temporal	Temporal	temporal_order	What happens after the historical scenes showing a towering rocket on a launch pad and significant events from NASA's historical archives?	[ "The video transitions to a NASA press conference or briefing with six individuals seated behind a long desk.", "The video shows a detailed shot of the shuttle Endeavour docked alongside a space station module.", "The video displays a blue screen featuring prominent text and logos related to a NASA event.", "...	B	1	0.25	videos/28a086858d1fbeee7c75f11362c7c3606d9dbbe16846550271f5f69ee2e57579.mp4	28a086858d1fbeee7c75f11362c7c3606d9dbbe16846550271f5f69ee2e57579	3,235	1,280	720	30/1	null	yt::HLV-1K::::MNdNUji38S0	videos/4707b6677b36c3bcd87eb77c5392b903b2347755ff9ca914e7471e0597c20ed7.mp4	MIT	null
SLVMBench_169	SLVMBench	temporal	Temporal	temporal_order	After warping the loom with the vertical threads, what are the next two major steps?	[ "Swivel the hooks to raise every other warp thread,and then weave the horizontal threads (weft) through the opening.", "Flip the hooks to raise alternating vertical threads ,and then begin weaving the weft threads through the warp.", "Weave the horizontal threads (weft) across the warp,and then flip the hooks t...	E	4	0.2	videos/8f06aa2e9776fc9a76c0dac902e4ba9298571b0da3ce78e8621d94908a1c3896.mp4	8f06aa2e9776fc9a76c0dac902e4ba9298571b0da3ce78e8621d94908a1c3896	42.372	1,280	720	8652800/433039	{ "codec": "aac", "sample_rate": "16000", "channels": 1 }	SLVMBench/SLVMBench::::videos/merged_short_videos/merged_v6ux3Bxrcc4_v6ux3Bxrcc4_end3_TxFpJ5y3RyU.mp4	videos/8f06aa2e9776fc9a76c0dac902e4ba9298571b0da3ce78e8621d94908a1c3896.mp4	Apache-2.0	null
Video-MME-v2_1611	Video-MME-v2	temporal	Temporal	temporal_order	In a secretary's office interview scenario, which of the following sequences of events is correct?	[ "Kevin enters the office → Allison enters the office → Secretary enters the office → Kevin is hired → Allison leaves the office.", "Allison enters the office → Kevin enters the office → Secretary enters the office → Allison is hired → Allison leaves the office.", "Kevin enters the office → Allison enters the of...	E	4	0.125	videos/b61feff1f80bd6db7d1702df77230f7762f956df47a9e2cc7e26b67f554a09b5.mp4	b61feff1f80bd6db7d1702df77230f7762f956df47a9e2cc7e26b67f554a09b5	842.443	1,920	1,080	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	MME-Benchmarks/Video-MME-v2::videos/021.zip::403.mp4	videos/b61feff1f80bd6db7d1702df77230f7762f956df47a9e2cc7e26b67f554a09b5.mp4	MIT	null
GUI-World_3228	GUI-World	temporal	Temporal	temporal_order	Which action is performed first in the video sequence?	[ "The Google homepage is refreshed.", "A 'New Tab' is opened.", "The 'New Tab' is closed.", "The mouse cursor moves to the address bar." ]	C	2	0.25	videos/62f298c2dc4197fb3ca167f51ba5262c82ff0a3bfba3a15ad3b330865809c91a.mp4	62f298c2dc4197fb3ca167f51ba5262c82ff0a3bfba3a15ad3b330865809c91a	7.333	1,280	720	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	ONE-Lab/GUI-World::::website/86.mp4	videos/62f298c2dc4197fb3ca167f51ba5262c82ff0a3bfba3a15ad3b330865809c91a.mp4	unknown	null
ALLVB_1040	ALLVB	temporal	Temporal	action_counting	How many times does Nicholas express his desire to leave the hospital in the meeting room scene?	[ "Once", "Twice", "Three times", "Four times", "Five times" ]	E	4	0.2	videos/46e8a4d072d16a49671a60783ca54aaf564132e31f833bdef0aa10a9cf2e1b77.mp4	46e8a4d072d16a49671a60783ca54aaf564132e31f833bdef0aa10a9cf2e1b77	7,364.778	1,280	536	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/The Son (2022)/The Son (2022).mp4	videos/46e8a4d072d16a49671a60783ca54aaf564132e31f833bdef0aa10a9cf2e1b77.mp4	CC-BY-NC-SA-4.0	null
TOC-Bench_289	TOC-Bench	temporal	Temporal	temporal_localization	Does magnets on fridge ever leave the frame in the video?	[ "magnets on fridge does leave the frame", "magnets on fridge never leave the frame" ]	A	0	0.5	videos/933bde101f8bb67659db1dc5a88a66f554e6571b2b99d084fb5da31136158ae9.mp4	933bde101f8bb67659db1dc5a88a66f554e6571b2b99d084fb5da31136158ae9	35.549	480	270	24/1	{ "codec": "aac", "sample_rate": "44100", "channels": 1 }	anonymous-video-benchmark/toc_bench::::videos/charades_564DX.mp4	videos/933bde101f8bb67659db1dc5a88a66f554e6571b2b99d084fb5da31136158ae9.mp4	custom	null
ALLVB_14547	ALLVB	temporal	Temporal	temporal_localization	How does the video transition from the Capulet mansion to the beach scene?	[ "Through a fade-out and fade-in effect.", "Through a time-lapse shot of the mansion.", "Through a direct cut with a sound bridge.", "Through a dissolve effect.", "Through a split-screen transition." ]	B	1	0.2	videos/073f7608d3f6492059704ffd164e4fb92a3d862a9e351e4d958e8ec1bcdbd93e.mp4	073f7608d3f6492059704ffd164e4fb92a3d862a9e351e4d958e8ec1bcdbd93e	7,210.666	1,280	534	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Romeo + Juliet (1996)/Romeo + Juliet (1996).mp4	videos/073f7608d3f6492059704ffd164e4fb92a3d862a9e351e4d958e8ec1bcdbd93e.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_3042	S-EMBER	temporal	Temporal	action_counting	After seasoning the food, how many times did I take the spoon out of the pot?	[ "You took the spoon out of the pot 3 times after seasoning the ingredients.", "You lifted the spoon out of the pot twice after seasoning the contents.", "You lifted the spoon out of the pot 4 times after you seasoned the food.", "You took the spoon out of the pot exactly once after adding the seasoning.", "...	E	4	0.2	videos/7c7b1e3dca8c5a6a23b5b7df8b3014fdef6eb2202170f487481759b428b38413.mp4	7c7b1e3dca8c5a6a23b5b7df8b3014fdef6eb2202170f487481759b428b38413	600	720	960	12/1	null	facebook/S-EMBER::::videos/1212755953818606_start_0.0_end_600.02.mp4	videos/7c7b1e3dca8c5a6a23b5b7df8b3014fdef6eb2202170f487481759b428b38413.mp4	CC-BY-NC-4.0	null
ALLVB_690	ALLVB	temporal	Temporal	action_counting	How many times does Gregory attempt to punch Smith during their confrontation?	[ "Once", "Twice", "Three times", "Four times", "Five times" ]	E	4	0.2	videos/b808e5e19c79d2eae6ef4178f8ed9a50da5f55ab2ddb872c13510bb06ddc7d2b.mp4	b808e5e19c79d2eae6ef4178f8ed9a50da5f55ab2ddb872c13510bb06ddc7d2b	8,295.621	1,280	532	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/The Matrix Reloaded (2003)/The Matrix Reloaded (2003).mp4	videos/b808e5e19c79d2eae6ef4178f8ed9a50da5f55ab2ddb872c13510bb06ddc7d2b.mp4	CC-BY-NC-SA-4.0	null
FAVOR-Bench_650	FAVOR-Bench	temporal	Temporal	temporal_order	After transferring the bottle to the left hand, what is the next immediate action?	[ "Right hand unscrews the bottle cap and places it on the table", "Left hand holds the cup handle to prepare for pouring juice", "The subject shifts position to the left", "Right hand retrieves the bottle to prepare for pouring", "Left hand continues to maintain a grip on the base" ]	C	2	0.2	videos/baea87a67d9ff1f5f489441b5acb84f5cc25008adb8a1f8dc52841e241f2660b.mp4	baea87a67d9ff1f5f489441b5acb84f5cc25008adb8a1f8dc52841e241f2660b	28.333	640	480	15/1	null	FAVOR-Bench/FAVOR::::videos/FAVOR-Bench/26k-11-2-3\|P1\|2770\|3194.mp4	videos/baea87a67d9ff1f5f489441b5acb84f5cc25008adb8a1f8dc52841e241f2660b.mp4	CC-BY-NC-SA-4.0	null
EgoSchema_256	EgoSchema	temporal	Temporal	temporal_order	Describe how c's actions transition from focusing on the book to the tablet. what key events signify this shift in focus?	[ "The subject's focus noticeably shifts away from the book, transitioning towards the tablet, as she carefully adjusts the camera position.", "The subject's focus shifts from the book to the tablet when she drops the pencil.", "The subject's focus evidently shifts from the book to the tablet as she persistently ...	E	4	0.2	videos/ffa7e02ee538ffc09fa84d2ae706720e75496fab72eaac9305ff5f5f5b0b929d.mp4	ffa7e02ee538ffc09fa84d2ae706720e75496fab72eaac9305ff5f5f5b0b929d	180	480	360	30/1	null	lmms-eval/egoschema::videos_chunked_01.zip::videos/84389a11-7dc2-4e1d-80b1-e44d8787424a.mp4	videos/ffa7e02ee538ffc09fa84d2ae706720e75496fab72eaac9305ff5f5f5b0b929d.mp4	MIT	null
S-EMBER_888	S-EMBER	temporal	Temporal	action_counting	How many times did I pull a wipe out from the Purell box?	[ "You pulled a wipe out two times.", "You pulled a wipe out one time.", "You pulled a wipe out four times.", "You pulled a wipe out five times.", "You pulled a wipe out three times." ]	D	3	0.2	videos/40abe89a3dd3dfc4f378652deeb9fcd45380d058855796d10c79d2727a6a6c7f.mp4	40abe89a3dd3dfc4f378652deeb9fcd45380d058855796d10c79d2727a6a6c7f	566.833	720	962	12/1	null	facebook/S-EMBER::::videos/665560723051381_start_0.0_end_566.854.mp4	videos/40abe89a3dd3dfc4f378652deeb9fcd45380d058855796d10c79d2727a6a6c7f.mp4	CC-BY-NC-4.0	null
SLVMBench_2201	SLVMBench	temporal	Temporal	temporal_order	After explaining that the first step is to cut off the damaged branches, what is the next concept the speaker introduces for treating the root rot?	[ "See if it's continuing to spread after treatment.", "Check whether the roots feel firm or mushy.", "Remove the plant from the pot and clean the roots.", "Apply a fungicide to the remaining healthy roots.", "Let the roots dry out before repotting in fresh soil." ]	A	0	0.2	videos/18b0183daffc55af87e2ce10bdff7701ef6cf62c0be792cd70a6a3a918f6c73b.mp4	18b0183daffc55af87e2ce10bdff7701ef6cf62c0be792cd70a6a3a918f6c73b	209.578	1,280	720	20/1	{ "codec": "aac", "sample_rate": "16000", "channels": 1 }	SLVMBench/SLVMBench::::videos/merged_short_videos/merged_kSG9EH0xqRI_kSG9EH0xqRI_end6_5lBJuP6Nzmc.mp4	videos/18b0183daffc55af87e2ce10bdff7701ef6cf62c0be792cd70a6a3a918f6c73b.mp4	Apache-2.0	null
VideoOdyssey_2437	VideoOdyssey	temporal	Temporal	temporal_order	After the referee appears in the video, when the players huddle together in a circle with their arms draped over each other's shoulders, what sound can be heard in the background?	[ "Players' chanting", "Audience singing", "Audience cheering", "Referee's whistle" ]	B	1	0.25	videos/499c3c759c3526c24652bd17e4292764323f241d829d3e7799fba61a46ba18c8.mp4	499c3c759c3526c24652bd17e4292764323f241d829d3e7799fba61a46ba18c8	5,990.493	1,280	720	25/1	{ "codec": "aac", "sample_rate": "44100", "channels": 2 }	maifoundations/VideoOdyssey::::videos/iBrCs_vYh4I.mp4	videos/499c3c759c3526c24652bd17e4292764323f241d829d3e7799fba61a46ba18c8.mp4	CC-BY-NC-SA-4.0	null
ALLVB_3868	ALLVB	temporal	Temporal	temporal_order	What is the sequence of actions that occur when Brooks starts his turn in the game of Celebrity?	[ "Brooks stands up, takes a paper, and starts giving clues.", "Brooks stands up, pauses the timer, and starts giving clues.", "Brooks stands up, takes a paper, and pauses the timer.", "Brooks stands up, takes a paper, and sings a clue.", "Brooks stands up, pauses the timer, and tells a story." ]	E	4	0.2	videos/9f98fd90c233785060871b0c27756e2b35361e693205c33dec1ccfdaeef3d5b4.mp4	9f98fd90c233785060871b0c27756e2b35361e693205c33dec1ccfdaeef3d5b4	6,005.76	1,280	534	13978/583	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Game Night (2018)/Game Night (2018).mp4	videos/9f98fd90c233785060871b0c27756e2b35361e693205c33dec1ccfdaeef3d5b4.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_6678	S-EMBER	temporal	Temporal	action_counting	How many times have I turned on the water so far?	[ "Four times.", "Two times.", "Six times.", "Three times.", "One time." ]	C	2	0.2	videos/b5fd6f7cafe6a490bac63cecea26e388b92729aca3dd80e56c749615cfe03c10.mp4	b5fd6f7cafe6a490bac63cecea26e388b92729aca3dd80e56c749615cfe03c10	600	720	966	12/1	null	facebook/S-EMBER::::videos/697356956032151_start_0.0_end_599.942.mp4	videos/b5fd6f7cafe6a490bac63cecea26e388b92729aca3dd80e56c749615cfe03c10.mp4	CC-BY-NC-4.0	null
S-EMBER_7291	S-EMBER	temporal	Temporal	action_counting	How many times have I pointed at the Lego box so far?	[ "You have pointed at the Lego box 3 times.", "You have pointed at the Lego box 0 times.", "You have pointed at the Lego box 2 times.", "You have pointed at the Lego box 5 times.", "You have pointed at the Lego box 1 time." ]	D	3	0.2	videos/ef0ad8eeb0219241dc1f742db24ce20a599520d33d226bfd44df635935ea7fa9.mp4	ef0ad8eeb0219241dc1f742db24ce20a599520d33d226bfd44df635935ea7fa9	319	720	958	12/1	null	facebook/S-EMBER::::videos/790220990097034_start_0.0_end_318.976.mp4	videos/ef0ad8eeb0219241dc1f742db24ce20a599520d33d226bfd44df635935ea7fa9.mp4	CC-BY-NC-4.0	null
TOC-Bench_2213	TOC-Bench	temporal	Temporal	speed_duration	How long does cherry stay in contact with cherry?	[ "very briefly", "for several seconds", "for an extended period", "cherry always stays in contact with cherry" ]	D	3	0.25	videos/4ca76babe6d7886a5e8ca7ae5e4c509c2c0d8d082a91eaf3603f3c14cb8e2249.mp4	4ca76babe6d7886a5e8ca7ae5e4c509c2c0d8d082a91eaf3603f3c14cb8e2249	7.333	1,920	1,080	12/1	null	anonymous-video-benchmark/toc_bench::::videos/mose_ir4bmq0e.mp4	videos/4ca76babe6d7886a5e8ca7ae5e4c509c2c0d8d082a91eaf3603f3c14cb8e2249.mp4	custom	null
ALLVB_9711	ALLVB	temporal	Temporal	action_counting	How many times does Melvin check the locks on his door in the scene where he is in his apartment with Verdell?	[ "Once", "Twice", "Three times", "Four times", "Five times" ]	E	4	0.2	videos/70eb153088b5a13c182765ed3902d9b018061380a0bb07196241837e0e05715b.mp4	70eb153088b5a13c182765ed3902d9b018061380a0bb07196241837e0e05715b	8,318.421	1,280	688	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/As Good as It Gets (1997)/As Good as It Gets (1997).mp4	videos/70eb153088b5a13c182765ed3902d9b018061380a0bb07196241837e0e05715b.mp4	CC-BY-NC-SA-4.0	null
UrbanVideo-Bench_53	UrbanVideo-Bench	temporal	Temporal	temporal_order	Where do you start and end your journey?	[ "Start at the row of trees lining the avenue and end at the supermarket with a large yellow sign.", "Start at the row of trees lining the avenue and end at the storefront with an All-Star awning.", "Start at the tall building with a glass facade and end at the row of trees lining the avenue.", "Start at the s...	E	4	0.2	videos/1c9ba75659494030ea4a95da03492887d3738b2703f199c51bb587560c16f9c4.mp4	1c9ba75659494030ea4a95da03492887d3738b2703f199c51bb587560c16f9c4	81.85	960	720	20/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/EmbodiedCity_46.mp4	videos/1c9ba75659494030ea4a95da03492887d3738b2703f199c51bb587560c16f9c4.mp4	MIT	null
S-EMBER_9230	S-EMBER	temporal	Temporal	speed_duration	How long did I point at the white hat next to the rope?	[ "You pointed at the white hat for about 3 seconds.", "You pointed at the white hat for about 10 seconds.", "You pointed at the white hat for about 2 seconds.", "You pointed at the white hat for about 15 seconds.", "You pointed at the white hat for about 5 seconds." ]	D	3	0.2	videos/4fe80921b274bb7f4278c77d505d58b1f5cbff9a43b2a0a2355939c3c0c2b45f.mp4	4fe80921b274bb7f4278c77d505d58b1f5cbff9a43b2a0a2355939c3c0c2b45f	315.417	720	404	12/1	null	facebook/S-EMBER::::videos/24311049685225309_start_0.0_end_315.432.mp4	videos/4fe80921b274bb7f4278c77d505d58b1f5cbff9a43b2a0a2355939c3c0c2b45f.mp4	CC-BY-NC-4.0	null
S-EMBER_826	S-EMBER	temporal	Temporal	speed_duration	After first placing the box on the roll of wrapping paper, how long did it take me to cut the paper?	[ "Approximately 13 seconds.", "Approximately 8 seconds.", "Approximately 15 seconds.", "Approximately 30 seconds.", "Approximately 25 seconds." ]	E	4	0.2	videos/eecae3a526dc7a898dedbf87c48a9ed60ba4ae2e584d15482c59692f6d970f2c.mp4	eecae3a526dc7a898dedbf87c48a9ed60ba4ae2e584d15482c59692f6d970f2c	300.167	720	954	12/1	null	facebook/S-EMBER::::videos/1238299771211414_start_0.0_end_300.127.mp4	videos/eecae3a526dc7a898dedbf87c48a9ed60ba4ae2e584d15482c59692f6d970f2c.mp4	CC-BY-NC-4.0	null
S-EMBER_3638	S-EMBER	temporal	Temporal	temporal_order	Right before I started walking, what did the black vehicle on my left do?	[ "It made a right turn and drove away.", "It drove straight past you along the street.", "It slowed down and pulled over to the curb.", "It made a U-turn in the middle of the street.", "It didn't move at all and remained parked." ]	D	3	0.2	videos/b22cf1b8284348e7a4e713b611c94b00e2d15139be9fb2ad4378bd0f0f6522e4.mp4	b22cf1b8284348e7a4e713b611c94b00e2d15139be9fb2ad4378bd0f0f6522e4	404.417	720	966	12/1	null	facebook/S-EMBER::::videos/1488201325493720_start_0.0_end_404.394.mp4	videos/b22cf1b8284348e7a4e713b611c94b00e2d15139be9fb2ad4378bd0f0f6522e4.mp4	CC-BY-NC-4.0	null
TOC-Bench_604	TOC-Bench	temporal	Temporal	temporal_order	Which event happens first in the video?	[ "glass with dark liquid gets partly hidden before yellow paper gets fully hidden", "yellow paper gets fully hidden before glass with dark liquid gets partly hidden" ]	B	1	0.5	videos/5b88a4706c5ba9b13575ab8addb1f48054b0c8cb30b945ce9c9810bd596cd71c.mp4	5b88a4706c5ba9b13575ab8addb1f48054b0c8cb30b945ce9c9810bd596cd71c	10.635	1,280	720	6001/200	{ "codec": "aac", "sample_rate": "44100", "channels": 1 }	anonymous-video-benchmark/toc_bench::::videos/perception_test_video_3316.mp4	videos/5b88a4706c5ba9b13575ab8addb1f48054b0c8cb30b945ce9c9810bd596cd71c.mp4	custom	null
K9-Bench_4337	K9-Bench	temporal	Temporal	temporal_order	Trace the interaction loop that develops after the dog makes repeated incorrect choices in the two-hand guessing game, leading to the human's final comforting gesture.	[ "Dog circles hands with low tail, barks once. Human opens correct hand. Dog places paw on arm, rests head on knee.", "Dog looks confused, growls softly at empty hand. Human points to correct hand. Dog sits close, leans on lap.", "Dog nudges empty hand repeatedly, whines softly. Human guides paw to correct hand....	E	4	0.2	videos/7c1cd2dec023730036acb0e4f0148b5669a009a85744a4161422d752e2a20dc5.mp4	7c1cd2dec023730036acb0e4f0148b5669a009a85744a4161422d752e2a20dc5	156.821	null	null	null	{ "codec": "opus", "sample_rate": "48000", "channels": 2 }	yt::K9-Bench::::IILr-MGWud8	videos/84c07d4228e4ed28dafdff9e96c89bc3491942e066a559f2a8b3167a9531ec3b.mp4	CC-BY-NC-4.0	null
S-EMBER_5054	S-EMBER	temporal	Temporal	speed_duration	What was the duration of time from when I first picked up the stylus to when I began using it on the tablet?	[ "About 4 seconds.", "About 3 seconds.", "About 2 seconds.", "0 seconds (no delay).", "About 5 seconds." ]	E	4	0.2	videos/485ab56a0944f6910ec362fcf3eca48a11851194d0f06fe2a1a7665e0614ce4e.mp4	485ab56a0944f6910ec362fcf3eca48a11851194d0f06fe2a1a7665e0614ce4e	443.333	720	958	12/1	null	facebook/S-EMBER::::videos/1649051239107188_start_0.0_end_443.293.mp4	videos/485ab56a0944f6910ec362fcf3eca48a11851194d0f06fe2a1a7665e0614ce4e.mp4	CC-BY-NC-4.0	null
S-EMBER_3231	S-EMBER	temporal	Temporal	action_counting	How many titles on the spine of the book did I point at before opening it?	[ "Two titles.", "Three titles.", "Five titles.", "Four titles.", "Six titles." ]	E	4	0.2	videos/e03d4191bba33bd3208ddaacb36d13dd906b3998a94e813e07d32517dfb8eed4.mp4	e03d4191bba33bd3208ddaacb36d13dd906b3998a94e813e07d32517dfb8eed4	344.5	720	960	12/1	null	facebook/S-EMBER::::videos/736081299227357_start_0.0_end_344.496.mp4	videos/e03d4191bba33bd3208ddaacb36d13dd906b3998a94e813e07d32517dfb8eed4.mp4	CC-BY-NC-4.0	null
S-EMBER_26	S-EMBER	temporal	Temporal	action_counting	How many times did I dip a brush into the pink paint bottle?	[ "2 times.", "1 time.", "4 times.", "3 times.", "5 times." ]	E	4	0.2	videos/9a7a1def3e5f525d04aa45225d0a871ab53369a6782e9e3912fcc386a82adfab.mp4	9a7a1def3e5f525d04aa45225d0a871ab53369a6782e9e3912fcc386a82adfab	352.167	720	958	12/1	null	facebook/S-EMBER::::videos/1026550696287614_start_0.0_end_352.19.mp4	videos/9a7a1def3e5f525d04aa45225d0a871ab53369a6782e9e3912fcc386a82adfab.mp4	CC-BY-NC-4.0	null
S-EMBER_7718	S-EMBER	temporal	Temporal	action_counting	How many times did I use the spoon to take out the liquid from this cup in my hand?	[ "Four times.", "Three times.", "Five times.", "Ten times.", "One time." ]	D	3	0.2	videos/d53de0c2f226c848ccbf0dab009e663d4e674ec2908d423e6ecfc8d5622e2b7a.mp4	d53de0c2f226c848ccbf0dab009e663d4e674ec2908d423e6ecfc8d5622e2b7a	600	720	966	12/1	null	facebook/S-EMBER::::videos/1621966575261017_start_0.0_end_599.982.mp4	videos/d53de0c2f226c848ccbf0dab009e663d4e674ec2908d423e6ecfc8d5622e2b7a.mp4	CC-BY-NC-4.0	null
S-EMBER_3823	S-EMBER	temporal	Temporal	action_counting	Since I closed the drawer on the nightstand, how many price tags have I touched?	[ "2 price tags.", "3 price tags.", "1 price tag.", "0 price tags.", "4 price tags." ]	E	4	0.2	videos/3e151934c2eb70677ccfa6af0a1bb9d62b2a5f7d81df6c4836818c641af63c8d.mp4	3e151934c2eb70677ccfa6af0a1bb9d62b2a5f7d81df6c4836818c641af63c8d	305.667	720	962	12/1	null	facebook/S-EMBER::::videos/750568127710505_start_0.0_end_305.655.mp4	videos/3e151934c2eb70677ccfa6af0a1bb9d62b2a5f7d81df6c4836818c641af63c8d.mp4	CC-BY-NC-4.0	null
S-EMBER_8655	S-EMBER	temporal	Temporal	action_counting	How many people have I seen walk into the Nintendo store?	[ "Four.", "Three.", "One.", "Nine.", "Two." ]	D	3	0.2	videos/e8663ac79e86be8cc3e94ac74fcb19204d724c86de256801f991f3a686e92dc4.mp4	e8663ac79e86be8cc3e94ac74fcb19204d724c86de256801f991f3a686e92dc4	600	720	954	12/1	null	facebook/S-EMBER::::videos/1439522597215124_start_0.0_end_600.004.mp4	videos/e8663ac79e86be8cc3e94ac74fcb19204d724c86de256801f991f3a686e92dc4.mp4	CC-BY-NC-4.0	null
FAVOR-Bench_1074	FAVOR-Bench	temporal	Temporal	temporal_order	Regarding the subject's two interactions with the same object, which of the following descriptions is correct?	[ "The subject uses the left hand to first open the drawer and then close the drawer", "The subject uses the left hand to first put down the cup and then move the cup", "The subject uses the right hand to first rinse the spoon and then shake the spoon", "The subject uses the right hand to first take out the spo...	B	1	0.2	videos/70ba3f9a57f9bbdc6feb136a5cb7d520ca4ae88569f30e23d8469f13ee68a175.mp4	70ba3f9a57f9bbdc6feb136a5cb7d520ca4ae88569f30e23d8469f13ee68a175	33.133	640	480	15/1	null	FAVOR-Bench/FAVOR::::videos/FAVOR-Bench/29k-11-3-2\|P1\|440\|936.mp4	videos/70ba3f9a57f9bbdc6feb136a5cb7d520ca4ae88569f30e23d8469f13ee68a175.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_5572	S-EMBER	temporal	Temporal	action_counting	So far, how many times have I used tweezers to peel off a sticker?	[ "5 times.", "3 times.", "2 times.", "15 times.", "4 times." ]	D	3	0.2	videos/ad509ccaf902226e1182d3c6a083096ab815eebd07646ecf5983043fe46b1625.mp4	ad509ccaf902226e1182d3c6a083096ab815eebd07646ecf5983043fe46b1625	600	720	958	12/1	null	facebook/S-EMBER::::videos/1199465581912902_start_0.0_end_600.014.mp4	videos/ad509ccaf902226e1182d3c6a083096ab815eebd07646ecf5983043fe46b1625.mp4	CC-BY-NC-4.0	null
ALLVB_15618	ALLVB	temporal	Temporal	temporal_order	How does the video transition from Amy's speech to the scene where she talks to Gwendolyn in her Range Rover?	[ "The scene fades to black and then opens with Gwendolyn crying.", "The camera pans from the auditorium to the parking lot.", "The scene cuts directly from the applause to Gwendolyn's car.", "The video shows a montage of moms leaving the auditorium.", "The scene transitions with a voiceover from Amy." ]	D	3	0.2	videos/b68a19223616844885cca5664b2f166d4cd51e16d3e2bd35b5c761c4f5830500.mp4	b68a19223616844885cca5664b2f166d4cd51e16d3e2bd35b5c761c4f5830500	6,057.013	1,280	534	13978/583	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Bad Moms (2016)/Bad Moms (2016).mp4	videos/b68a19223616844885cca5664b2f166d4cd51e16d3e2bd35b5c761c4f5830500.mp4	CC-BY-NC-SA-4.0	null
UrbanVideo-Bench_4657	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	You are navigating to the balcony on the top floor of the building in front of you, where white clothes are hanging. What is the correct summary of your trajectory from the beginning to the current location?	[ "I start from the parking lot, rise upward, move toward the building, and reach my current location.", "I start from the street, move forward, then rise to the height of the building and move toward the balcony.", "I start from the ground, fly over the street, move to the top floor, and then move to the designa...	E	4	0.2	videos/0bd067b9b04a929c60e54dae7319c63fe3c315c1d59531d2938659ea044d2a6b.mp4	0bd067b9b04a929c60e54dae7319c63fe3c315c1d59531d2938659ea044d2a6b	64.2	1,280	720	15/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/RealWorld_GN_7_2.mp4	videos/0bd067b9b04a929c60e54dae7319c63fe3c315c1d59531d2938659ea044d2a6b.mp4	MIT	null
S-EMBER_8015	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	How do I get back to the aisle with the white Threshold pillows?	[ "Head back to the main cross-aisle and look for the endcap with the large pillow sign; turn into that row to find the white pillows on the left-hand shelves.", "Turn around and walk back down the aisle you came from, then turn left at the first intersection to reach the aisle with the white Threshold pillows.", ...	E	4	0.2	videos/9e6e0525976a7674c698bba459331c3855abff0b1d911bba538fffcfbbe27382.mp4	9e6e0525976a7674c698bba459331c3855abff0b1d911bba538fffcfbbe27382	300	720	540	12/1	null	facebook/S-EMBER::::videos/2048202589040619_start_0.0_end_300.0.mp4	videos/9e6e0525976a7674c698bba459331c3855abff0b1d911bba538fffcfbbe27382.mp4	CC-BY-NC-4.0	null
VITATECS_1478	VITATECS	spatial_physical	Spatial / physical	spatial_relation	Which caption correctly describes what happens in the video?	[ "a young girl runs away from her gymnastics pad", "a young girl runs towards her gymnastics pad" ]	A	0	0.5	videos/efd4d32010c6740ab3f0aef64ecb278e0e757c23a6090e464d2f6bf10095cad3.mp4	efd4d32010c6740ab3f0aef64ecb278e0e757c23a6090e464d2f6bf10095cad3	13.981	320	240	30000/1001	null	lscpku/VITATECS::vitatecs_videos.zip::MSRVTT/video9771.mp4	videos/efd4d32010c6740ab3f0aef64ecb278e0e757c23a6090e464d2f6bf10095cad3.mp4	CC-BY-4.0	null
S-EMBER_283	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	From here, how do I get back to where I pointed at the large tree that was blocking the sun?	[ "Go back the way you came, turn right at the intersection, and walk along the main path straight ahead until you find the tree.", "Turn around and walk straight down the dirt path without making any turns to get back to where the tree blocked the sun.", "Walk back along the current narrow path to the main dirt ...	E	4	0.2	videos/ad5de5eb87fd122818b67a73b3a601738bd78611673cafdb558ef8d966c22379.mp4	ad5de5eb87fd122818b67a73b3a601738bd78611673cafdb558ef8d966c22379	313.833	720	962	12/1	null	facebook/S-EMBER::::videos/1053473496549619_start_0.0_end_313.82.mp4	videos/ad5de5eb87fd122818b67a73b3a601738bd78611673cafdb558ef8d966c22379.mp4	CC-BY-NC-4.0	null
MMSI-Video_227	MMSI-Video	spatial_physical	Spatial / physical	spatial_relation	When preparing to go down the stairs, in which direction are the bedroom and living room respectively?	[ "Bedroom on the right, living room on the left", "Both on the left side", "Bedroom on the left, living room on the right", "Both on the right side" ]	B	1	0.25	videos/138c4546f07a10b21a1de51e8f9e225df9fb8fcad55e347b3f86cbf4fa0997a6.mp4	138c4546f07a10b21a1de51e8f9e225df9fb8fcad55e347b3f86cbf4fa0997a6	188.333	640	360	3/1	null	oscarqjh/MMSI-Video-Bench_lmmseval::videos.zip::videos/question_0184/room3d_0236_0.mp4	videos/138c4546f07a10b21a1de51e8f9e225df9fb8fcad55e347b3f86cbf4fa0997a6.mp4	CC-BY-4.0	null
UrbanVideo-Bench_4973	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	You are navigating to the "Huaji Stone Rice Rice Roll" store. What is the correct summary of your trajectory from the beginning to the current location?	[ "Start from the parking lot, move forward to the street, and then fly to the current position above the store.", "Start from a high-rise building, descend to a shop, and move to the current location.", "Start from the parking lot, rise to the height of the high-rise building, move along the street, and reach th...	E	4	0.2	videos/185ec66e2af2835fc4bf6c50a3e4a2285fbb04ed6138ceb14e8a3b2df0b43290.mp4	185ec66e2af2835fc4bf6c50a3e4a2285fbb04ed6138ceb14e8a3b2df0b43290	29.733	1,280	720	15/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/RealWorld_GN_20_0.mp4	videos/185ec66e2af2835fc4bf6c50a3e4a2285fbb04ed6138ceb14e8a3b2df0b43290.mp4	MIT	null
VF-Eval_2358	VF-Eval	spatial_physical	Spatial / physical	physics_causality	Please assess the video and identify any quality issues, such as blurry visuals, low resolution, or distortion.	[ "The color grading of the video changes naturally as it progresses, but it should remain consistent.", "The video’s focus remains excessively sharp around the edges, creating an unnatural visual effect.", "The resolution of the video remains constant throughout, but subtle pixelation occurs in the foreground de...	D	3	0.25	videos/39f4e73247429f84fd6bfabd20eeff704053770b85acd23e6dd70de2d200a857.mp4	39f4e73247429f84fd6bfabd20eeff704053770b85acd23e6dd70de2d200a857	4	512	320	8/1	null	songtingyu/vf-eval::videos.zip::videos/data/video-data/lavie/data/lavie/data/lavie_38_A_round_buoy_floats_on_the_surface_of_the_ocean._1.mp4	videos/39f4e73247429f84fd6bfabd20eeff704053770b85acd23e6dd70de2d200a857.mp4	MIT	null
ALLVB_7117	ALLVB	spatial_physical	Spatial / physical	physics_causality	What is the outcome when Adonis throws a three-punch combo at Vitor?	[ "Vitor is knocked down.", "The crowd boos.", "Vitor counters with a powerful punch.", "The punches have no effect.", "Adonis gets hit by Vitor's right hand." ]	B	1	0.2	videos/178922cb2f2cc9b7f8ff0f5a456ca3d00cb3d0537ab9740bdbcbd5d9d4e4c810.mp4	178922cb2f2cc9b7f8ff0f5a456ca3d00cb3d0537ab9740bdbcbd5d9d4e4c810	7,800.468	1,280	534	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Creed II (2018)/Creed II (2018).mp4	videos/178922cb2f2cc9b7f8ff0f5a456ca3d00cb3d0537ab9740bdbcbd5d9d4e4c810.mp4	CC-BY-NC-SA-4.0	null
ALLVB_23938	ALLVB	spatial_physical	Spatial / physical	physics_causality	How does Ted's action of lifting Athena's heavy bag impact his environment?	[ "It causes the bellhop cart to break.", "It makes the taxi driver leave in a hurry.", "It results in Ted knocking over a vase in the lobby.", "It leads to Ted injuring his back.", "It causes a commotion that attracts other guests." ]	B	1	0.2	videos/95e83085a7e3d762f4a5134c532a27343db04e7a5acda8f0cf01c947c78e4d36.mp4	95e83085a7e3d762f4a5134c532a27343db04e7a5acda8f0cf01c947c78e4d36	5,868.544	1,280	690	24000/1001	{ "codec": "aac", "sample_rate": "48000", "channels": 2 }	ALLVB/ALLVB::::test_set_movie/Four Rooms (1995)/Four Rooms (1995).mp4	videos/95e83085a7e3d762f4a5134c532a27343db04e7a5acda8f0cf01c947c78e4d36.mp4	CC-BY-NC-SA-4.0	null
SIS-Bench_1075	SIS-Bench	spatial_physical	Spatial / physical	spatial_relation	Starting from the beginning of the video, with the drone overlooking high-rise residential buildings and streets, what action sequence should the drone execute to reach the central fountain in the square?	[ "First, yaw left 90 degrees, then fly forward, and finally descend to above the fountain.", "First, yaw left 180 degrees, then fly forward, and finally descend to above the fountain.", "First, yaw left 90 degrees, then yaw right 180 degrees, then fly forward, and finally descend to above the fountain.", "Firs...	D	3	0.25	videos/7098710fb1b7f8ce42abfa4537afa06c710574973a22ff3d7cfa006512b1bd03.mp4	7098710fb1b7f8ce42abfa4537afa06c710574973a22ff3d7cfa006512b1bd03	59.467	1,280	720	15/1	null	choucsan/SIS-Bench::::video/UrbanVideo/UrbanVideo_0153.mp4	videos/7098710fb1b7f8ce42abfa4537afa06c710574973a22ff3d7cfa006512b1bd03.mp4	Apache-2.0	null
SIS-Bench_558	SIS-Bench	spatial_physical	Spatial / physical	spatial_relation	What object is located to the rear of the yellow and white low-rise building?	[ "The high-rise building with the \"阳光城檀府\" sign", "The shop with the blue-green billboard \"深圳市居众装饰集团\"", "The blue swimming pool", "The high-rise building with red walls and gray-white patterns" ]	C	2	0.25	videos/3af230e0b0d23d5cc882800a3e12bfa89bfc828fd3b4433bfea521363ea1baec.mp4	3af230e0b0d23d5cc882800a3e12bfa89bfc828fd3b4433bfea521363ea1baec	5.375	1,280	720	24/1	null	choucsan/SIS-Bench::::video/AirScape/AirScape_0226.mp4	videos/3af230e0b0d23d5cc882800a3e12bfa89bfc828fd3b4433bfea521363ea1baec.mp4	Apache-2.0	null
S-EMBER_7308	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	How can I get to the carousel entrance from here?	[ "Walk straight ahead down the walkway and turn right at the very first corner you reach.", "Walk straight ahead along the path, and the carousel entrance will be clearly on your right.", "Walk straight along the path through the park, passing the library building on your right side.", "Step back, turn right, ...	D	3	0.2	videos/9f98f18c276db7a9d14d0a8827938c1fc40e120329c3ca99b77423938622c0df.mp4	9f98f18c276db7a9d14d0a8827938c1fc40e120329c3ca99b77423938622c0df	600	720	966	12/1	null	facebook/S-EMBER::::videos/695325632865279_start_0.0_end_599.959.mp4	videos/9f98f18c276db7a9d14d0a8827938c1fc40e120329c3ca99b77423938622c0df.mp4	CC-BY-NC-4.0	null
TimeBlind_1929	TimeBlind	spatial_physical	Spatial / physical	spatial_relation	Is the player's badminton racket touching the net?	[ "The racket does not appear to be touching the net.", "The racket is clearly touching the net." ]	B	1	0.5	videos/e659c63e0aba0c1786fb8533bcbf612ea538ce1edbca276c1b1cc485974fc5d9.mp4	e659c63e0aba0c1786fb8533bcbf612ea538ce1edbca276c1b1cc485974fc5d9	5	720	1,280	30/1	{ "codec": "aac", "sample_rate": "44100", "channels": 1 }	BaiqiL/TimeBlind::::videos/mcq_vid_00182_1.mp4	videos/e659c63e0aba0c1786fb8533bcbf612ea538ce1edbca276c1b1cc485974fc5d9.mp4	unknown	null
UrbanVideo-Bench_3112	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	Navigation Instruction given at initial position: [now take off and turn right and fly over the pond and closer the white building. now go over the buildings and turn left. now go over the road and buildings and move closer to the white building. now get little down and turn back and go forward until the grey building ...	[ "I go over the road and buildings and approach the white building.", "I turn around.", "I fly over the pond and approach the white building.", "I turn right and fly across the pond.", "I take off and turn right." ]	B	1	0.2	videos/ccd01d3b303c5e738a0034fdfeb15159be91e303c33b0890a4212d1a02cf4c07.mp4	ccd01d3b303c5e738a0034fdfeb15159be91e303c33b0890a4212d1a02cf4c07	108	512	512	1/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/AerialVLN_50_3E13VNJ1NWTVCLLIDLD3F17T8BN1I3_3.mp4	videos/ccd01d3b303c5e738a0034fdfeb15159be91e303c33b0890a4212d1a02cf4c07.mp4	MIT	null
UrbanVideo-Bench_4351	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	Navigation Instruction given at initial position: [Raise the altitude, fly over the opposite road, and fly in the direction of the mountains]. At the initial position, you are asked to navigate according to a series of movement instructions. When you arrive at your current location, what is the direction to this row of...	[ "I am located behind a row of buses.", "I am located next to the bus row.", "I am located in front of the bus row.", "I am parked directly above the row of buses.", "I am far away from the bus row." ]	E	4	0.2	videos/59e6228603c471f7c4651dc7a94fbaf6168525c30ae7250e50b3a25acfa1c02d.mp4	59e6228603c471f7c4651dc7a94fbaf6168525c30ae7250e50b3a25acfa1c02d	150	1,280	720	15/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/RealWorld_RN_12_9.mp4	videos/59e6228603c471f7c4651dc7a94fbaf6168525c30ae7250e50b3a25acfa1c02d.mp4	MIT	null
MotionBench_1601	MotionBench	spatial_physical	Spatial / physical	physics_causality	Does the wire fence influence the wolf's movement path?	[ "No, but the wolf interacts with it", "Yes, the wolf jumps over the fence", "No, the wolf moves independently of the fence", "Yes, it guides the wolf's entire path" ]	D	3	0.25	videos/9936feb4b516f379cb25bee1c5a785d51559c1e5a0fc168f8cbb307a786e332e.mp4	9936feb4b516f379cb25bee1c5a785d51559c1e5a0fc168f8cbb307a786e332e	16.517	1,920	1,080	30000/1001	null	zai-org/MotionBench::::MotionBench/self-collected/cOp9GCEZchPiUyuK.mp4	videos/9936feb4b516f379cb25bee1c5a785d51559c1e5a0fc168f8cbb307a786e332e.mp4	CC-BY-NC-SA-4.0	null
S-EMBER_8250	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	From where I am now, how do I get back to the bathroom?	[ "Turn around, walk back up the hallway you just came through and step into the first doorway on your right.", "You are already in the bathroom, as shown by the sink, mirror, and toilet visible in your current location.", "Turn around and walk back down the hallway toward the white door just outside the kitchen ...	D	3	0.2	videos/3b466507d56287f2f94eda5717cd186abbe4f6affce6e42dc9943f39066fc37f.mp4	3b466507d56287f2f94eda5717cd186abbe4f6affce6e42dc9943f39066fc37f	347.833	720	962	12/1	null	facebook/S-EMBER::::videos/2972728916243037_start_0.0_end_347.803.mp4	videos/3b466507d56287f2f94eda5717cd186abbe4f6affce6e42dc9943f39066fc37f.mp4	CC-BY-NC-4.0	null
S-EMBER_4991	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	How do I get back to the rack of cabinet samples I looked at earlier?	[ "Turn around and walk past the modern kitchen display and the KitchenAid sign.", "Head towards the left side of the room near the entrance of the kitchen area.", "Turn around and walk past the white kitchen display on your left, heading straight.", "Turn around and walk back down the aisle you came from, look...	E	4	0.2	videos/d7713e39ee7d1e3b80273db1d8e63791706192276e87e4f422b24888f473a10b.mp4	d7713e39ee7d1e3b80273db1d8e63791706192276e87e4f422b24888f473a10b	313.917	720	966	12/1	null	facebook/S-EMBER::::videos/963250449308085_start_0.0_end_313.911.mp4	videos/d7713e39ee7d1e3b80273db1d8e63791706192276e87e4f422b24888f473a10b.mp4	CC-BY-NC-4.0	null
UrbanVideo-Bench_4930	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	At the initial position, you are asked to navigate to a seller's store behind a nearby bus stop. Given the next steps for the parking lot entrance next to the store, what's next for you?	[ "I rise.", "I hover.", "I fly forward.", "I turn left.", "I turn right.", "I move backward.", "I decline." ]	G	6	0.142857	videos/b5b5d9e760effa391494b72f34d40d509cd4352950d2d3cf1684770dd84e6a9f.mp4	b5b5d9e760effa391494b72f34d40d509cd4352950d2d3cf1684770dd84e6a9f	92.267	1,280	720	15/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/RealWorld_GN_18_1.mp4	videos/b5b5d9e760effa391494b72f34d40d509cd4352950d2d3cf1684770dd84e6a9f.mp4	MIT	null
FAVOR-Bench_146	FAVOR-Bench	spatial_physical	Spatial / physical	spatial_relation	When the man picks up the clothes and opens the door, what is the camera movement method?	[ "The lens pans right", "Fast zoom", "Unstable camera shake", "Lens rotation", "Remain stationary" ]	C	2	0.2	videos/b4273047091d90a2b813569e853f07f48ba3b4ecd2e72388ab19fe0e062479b5.mp4	b4273047091d90a2b813569e853f07f48ba3b4ecd2e72388ab19fe0e062479b5	30.511	1,920	1,080	30000/1001	{ "codec": "aac", "sample_rate": "44100", "channels": 1 }	FAVOR-Bench/FAVOR::::videos/FAVOR-Bench/0GH5O.mp4	videos/b4273047091d90a2b813569e853f07f48ba3b4ecd2e72388ab19fe0e062479b5.mp4	CC-BY-NC-SA-4.0	null
UrbanVideo-Bench_1010	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	At the initial position, you are asked to navigate to the 15th floor balcony. At your current location, if the balcony on the 15th floor is not within your field of view, what is the most relevant object in your field of view, and where is this object?	[ "I cannot see the balcony on the 15th floor, but the main entrance of the high-rise building is in the lower part of my view.", "I can already see the balcony on the 15th floor.", "I cannot see the balcony on the 15th floor, but the entire high-rise building is in the center of my view.", "I cannot see the ba...	B	1	0.2	videos/d844ef0561674a75c59d2623db65d1370a8f0600218c78632e2946d4602fbc1a.mp4	d844ef0561674a75c59d2623db65d1370a8f0600218c78632e2946d4602fbc1a	73.05	960	720	20/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/EmbodiedCity_18_2.mp4	videos/d844ef0561674a75c59d2623db65d1370a8f0600218c78632e2946d4602fbc1a.mp4	MIT	null
UrbanVideo-Bench_2432	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	Navigation Instruction given at initial position: [fly through the medal bars at the beginning. fly down to the tree in the center of the water. make a stop at the bridge over the water. go to the car wash bill board and make a left. go to the coca cola cap and make a right. finish at the park. back to the bridge over ...	[ "I turn back to the bridge over the water.", "I go to the car wash billboard and turn left.", "I go to the Coca-Cola bottle cap and turn right.", "I stop at the bridge over the water.", "I go up the tall building." ]	E	4	0.2	videos/d68d218a16246174730efffdec6058963a6a257313eea04a91019ad8acde997f.mp4	d68d218a16246174730efffdec6058963a6a257313eea04a91019ad8acde997f	255	512	512	1/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/AerialVLN_15_3YMTUJH0D1E2DYYCUFV9R6G5V9TT4Z_4.mp4	videos/d68d218a16246174730efffdec6058963a6a257313eea04a91019ad8acde997f.mp4	MIT	null
UrbanVideo-Bench_1130	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	At the initial position, you are asked to navigate to the 8th floor balcony. At your current location, if the balcony on the 8th floor is not within your field of view, what is the most relevant object in your field of view, and where is this object?	[ "I cannot see the balcony on the 8th floor, but the main body of the high-rise building is to the right of the center of my field of view.", "I can already see the balcony on the 8th floor.", "I cannot see the balcony on the 8th floor, but there is a high-rise building in the center of my field of view.", "I ...	B	1	0.2	videos/07cf46e6f8cc76ec5a172de9c5fc1a45c122c7c773676cf81ebd60988ffbdb55.mp4	07cf46e6f8cc76ec5a172de9c5fc1a45c122c7c773676cf81ebd60988ffbdb55	42.05	960	720	20/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/EmbodiedCity_25_1.mp4	videos/07cf46e6f8cc76ec5a172de9c5fc1a45c122c7c773676cf81ebd60988ffbdb55.mp4	MIT	null
S-EMBER_1358	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	How do I get back to the bank from here?	[ "The video does not provide enough visual information to find a bank from here.", "Turn around and make the first left; the bank will be on your left.", "Turn around and walk straight back; the bank will be on your right.", "Walk straight ahead along the sidewalk; the bank will be on your left.", "Walk stra...	B	1	0.2	videos/4d04ef6c562bd9161dfedc4af605817792e2c88647f37022b9cca165219e321c.mp4	4d04ef6c562bd9161dfedc4af605817792e2c88647f37022b9cca165219e321c	600	720	966	12/1	null	facebook/S-EMBER::::videos/3076749645808628_start_0.0_end_600.014.mp4	videos/4d04ef6c562bd9161dfedc4af605817792e2c88647f37022b9cca165219e321c.mp4	CC-BY-NC-4.0	null
S-EMBER_1548	S-EMBER	spatial_physical	Spatial / physical	spatial_relation	Where did the man with the glasses place his phone before handing me seven of my shares for Western Publishing?	[ "On the desk in front of him.", "On the small round side table.", "On his lap between his knees.", "On the table to his right side.", "On the floor to his left side." ]	E	4	0.2	videos/95d2bd99d0f2aea8742dbd58e729549cbe39fd77dc88555dcd059ccb3c1fdd85.mp4	95d2bd99d0f2aea8742dbd58e729549cbe39fd77dc88555dcd059ccb3c1fdd85	1,200	720	958	12/1	null	facebook/S-EMBER::::videos/1419684649214709_start_0.0_end_1199.981.mp4	videos/95d2bd99d0f2aea8742dbd58e729549cbe39fd77dc88555dcd059ccb3c1fdd85.mp4	CC-BY-NC-4.0	null
SIS-Bench_972	SIS-Bench	spatial_physical	Spatial / physical	spatial_relation	Starting from the beginning of the video with the drone hovering above the main road and facing directly towards the high-rise residential area and street ahead, what action sequence should the drone execute to reach the red-roofed pavilion on the right side?	[ "Maintain altitude and fly forward, yaw left 45 degrees, and finally fly forward to near the pavilion.", "Maintain altitude and fly forward, yaw right 90 degrees, and finally fly forward to near the pavilion.", "Maintain altitude and fly forward, yaw right 90 degrees, then yaw left 45 degrees to align with the ...	A	0	0.25	videos/f233f7cf207e8be16b6896913ae296d64f58a11481fc0661c6a265425bbe48d8.mp4	f233f7cf207e8be16b6896913ae296d64f58a11481fc0661c6a265425bbe48d8	59.8	1,280	720	15/1	null	choucsan/SIS-Bench::::video/UrbanVideo/UrbanVideo_0073.mp4	videos/f233f7cf207e8be16b6896913ae296d64f58a11481fc0661c6a265425bbe48d8.mp4	Apache-2.0	null
UrbanVideo-Bench_962	UrbanVideo-Bench	spatial_physical	Spatial / physical	spatial_relation	At the initial position, you are asked to navigate to the 17th floor balcony. At the current location, if the balcony on the 17th floor is not within your field of view, what is the most relevant object in your field of view, and where is this object?	[ "I can't see the balcony on the 17th floor, but I can see the main entrance of the target building in the lower part of my field of view.", "I can already see the balcony on the 17th floor.", "I can't see the balcony on the 17th floor, but the front of the high-rise building is in the center of my field of view...	B	1	0.2	videos/2bd4efb775987de3f3854a5778d345111652308d678c91e5172584e7a5959f60.mp4	2bd4efb775987de3f3854a5778d345111652308d678c91e5172584e7a5959f60	38.8	960	720	20/1	null	EmbodiedCity/UrbanVideo-Bench::::videos/EmbodiedCity_16_1.mp4	videos/2bd4efb775987de3f3854a5778d345111652308d678c91e5172584e7a5959f60.mp4	MIT	null
M^3-Verse_1456	M^3-Verse	spatial_physical	Spatial / physical	metric_scale_estimation	The video shows two observations of the same indoor scene played back to back: first the first state (first observation), then the second state (second observation). How far was the salt shaker moved between the first observation and the second observation?	[ "No correct option is listed.", "7.10m - 9.92m", "1.42m - 4.25m", "4.26m - 7.09m" ]	B	1	0.25	videos/555764dc37d62ff410231031d1ce55f352abe9f66726bb4dd26d89a306acc126.mp4	555764dc37d62ff410231031d1ce55f352abe9f66726bb4dd26d89a306acc126	69.5	1,024	768	30/1	null	local::M^3-Verse::::local copy	videos/555764dc37d62ff410231031d1ce55f352abe9f66726bb4dd26d89a306acc126.mp4	unknown	null

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Video-Index v1.1

Video-Index v1.0 · GitHub · Paper

150 multiple-choice video questions selected from the 840 of Video-Index v1.0 for evaluating agents. Each question comes with its original source video: original resolution, frame rate and audio track. The agent receives the video file and decides how to inspect it.

How v1.1 was built

Remove what frontier agents already solve. Four agents answered the 840 v1.0 questions on the v1.0 videos (GPT-6-Astra, Claude Fable 5.1, Claude Opus 5.5, Gemini 4 Argon). We removed the 454 questions that all four answered correctly. For the 102 questions without Fable and Astra answers, we removed the 84 that Opus 5.5 and Gemini 4 both answered correctly.
Check questions that every agent missed. 77 questions were answered wrongly by all four agents. We removed the 37 where all four chose the same wrong option. A person watched the remaining 40 and kept 18: 14 with a correct answer key and 4 with a corrected key. The other 22 were removed as ambiguous or not decidable from the video.
Original videos. We fetched the original source video of the remaining 243 questions from the source benchmarks and removed the 9 questions whose video could no longer be retrieved. That left 234 questions.
Remove what the top three agents solve with the original video. 21 agents answered the 234 questions with the original videos (protocol below). We removed the 84 questions that all of the top three answered correctly: Claude Opus 5.5, Gemini 4 Argon and GPT-6-Astra. That left the 150 questions here.

The 150 questions cover 36 source benchmarks: 35 perception, 37 temporal, 39 spatial and physical, and 39 reasoning and knowledge. 70 videos have an audio track. Two answer keys differ from v1.0 (field answer_v1_0).

Agent protocol

Input. The original video as video.mp4 in the working directory. Nothing is pre-extracted, and there is no limit on resolution or frame rate.
Tools. A shell with ffmpeg/ffprobe and Python (OpenCV, Pillow, NumPy, and faster-whisper with local Whisper large-v3 and small models). Each CLI also has its own image viewer. In Gemini CLI, read_file also opens audio files.
Rules. No web search, web fetch or downloads. One attempt per question, 3600 seconds per question. A timeout or an error counts as wrong.
Harnesses.
- Claude models: Claude Code 2.1.300, reasoning effort max.
- Gemini models: Gemini CLI 0.57; Gemini 3.8 Flash and 3.6 Flash use 0.64.
- OpenAI models: Codex CLI 0.154.0, reasoning effort max.

Scores, cost per question and the construction statistics are on GitHub. The best agent, Claude Opus 5.5, answers 46.7% correctly.

Files

Path	Content
`items/test.jsonl`	one question per line (fields below)
`videos/<video_id>.<ext>`	the original source video of the question
`traces/<model>.tar.gz`	the agent trace of each of the 21 agents on every question (text only, see below)

Fields of items/test.jsonl. Fields shared with v1.0 keep their meaning, except that video, video_id and duration_s refer to the original video.

Field	Meaning
`item_id`	unique id, `<source benchmark>_<n>`, the same as in v1.0
`benchmark`	source benchmark
`capability_group`, `capability_group_label`	one of `perception`, `temporal`, `spatial_physical`, `reasoning_knowledge`
`fine_category`	fine capability category
`question`, `options`	question text and option texts, lettered A, B, ... in this order
`answer`, `answer_idx`	correct option letter and its index in `options`
`answer_v1_0`	the v1.0 answer key, present only where v1.1 corrected it
`chance`	1 / number of options
`video`, `video_id`	path of the original video in this repository and its SHA-256
`duration_s`, `width`, `height`, `fps`, `audio`	properties of the original video; `audio` is null when there is no audio track
`source_video`	where the original video comes from: `<HF dataset>::<archive>::<file>`, or a YouTube id
`video_v1_0`	path of the normalized video of this question in Video-Index v1.0
`license`	licence of the source benchmark

Traces

traces/<model>.tar.gz holds one directory per question, <model>/<item_id>/. Each directory has:

prompt.txt and command.json
the full event trace: stdout.jsonl for Claude Code and Codex, or events.jsonl for Gemini CLI. It records every tool call with its arguments and output, the model's messages, and token usage.
result.json with the prediction, the answer key, timing, token usage and cost
stderr.txt

Images the agents viewed are replaced by their SHA-256 and size, and frames or audio the agents extracted are not included. Cluster paths and user names are replaced with placeholders, and credentials with [REDACTED].

Loading

from datasets import load_dataset
from huggingface_hub import hf_hub_download

ds = load_dataset("Video-Index/Video-Index-v1-1", split="test")
item = ds[0]
video = hf_hub_download("Video-Index/Video-Index-v1-1", item["video"], repo_type="dataset")

Licences

Every question keeps the licence of its source benchmark (field license). The questions and videos are redistributed for research evaluation only; check the terms of the source benchmark before any other use.

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Paper for Video-Index/Video-Index-v1-1

Video-Index: A Curated Meta-Benchmark for Video Understanding

Paper • 2610.00960 • Published 28 days ago