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01
cavqa
camera_depth
video_frame_sequence
How far away is the painting?
1.48 m
How far away is the painting?
1.48m
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。
5
[5]
cavqa:00000-of-01024:100:99
00000-of-01024:100
cc-by-nc-nd-4.0
00e9cb1f9c1b478bf49e08fea4d88e486794cfc1
{"repo_id": "apple/ml-cubifyanything", "source_file": "cavqa_regression-train.tfrecord-00000-of-01024", "source_line": 8218}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4]], "video_frame_groups": [[0, 1, 2, 3, 4]], "modality_evidence": "cavqa_support_frames_reference_last", "timing_available": false, "reference_image_index": 4}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
0a64c8156b0537624ce3ede6c64ac0612591890f0d824a2b05adf2324ce54795
02
cavqa
height
video_frame_sequence
How tall is the book?
9 cm
How tall is the book?
9cm
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。
5
[5]
cavqa:00000-of-01024:102:28
00000-of-01024:102
cc-by-nc-nd-4.0
00e9cb1f9c1b478bf49e08fea4d88e486794cfc1
{"repo_id": "apple/ml-cubifyanything", "source_file": "cavqa_regression-train.tfrecord-00000-of-01024", "source_line": 8259}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4]], "video_frame_groups": [[0, 1, 2, 3, 4]], "modality_evidence": "cavqa_support_frames_reference_last", "timing_available": false, "reference_image_index": 4}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
fb6ef4ff56ba45cceb936a6522b50dbf0a97fdbc19ed23dce5f9af20affc4f7c
03
cavqa
length
video_frame_sequence
What is the length of vacuum cleaner?
32 cm
What is the length of vacuum cleaner?
32cm
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。
5
[5]
cavqa:00000-of-01024:111:20
00000-of-01024:111
cc-by-nc-nd-4.0
00e9cb1f9c1b478bf49e08fea4d88e486794cfc1
{"repo_id": "apple/ml-cubifyanything", "source_file": "cavqa_regression-train.tfrecord-00000-of-01024", "source_line": 9134}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4]], "video_frame_groups": [[0, 1, 2, 3, 4]], "modality_evidence": "cavqa_support_frames_reference_last", "timing_available": false, "reference_image_index": 4}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
ca577582819ae5d497e68175db68941cad411e5fd98957ed856a25619594d6c6
04
spacevista
area
video_frame_sequence
Estimate the floor space of the room visible in the footage (in square meters).
20 m2
Estimate the floor space of the room visible in the footage (in square meters).
20
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。
32
[32]
spacevista:1001419
DL3DV_7c41e7155aa05d64090ca2dda07f50cb38c0cdc7777296fc08e9cf6f9b708a3e
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1001420}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]], "video_frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30...
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
d76f0d7d80d2318169a2ac026b9a3e96b214c1f477fe441c5f7b893e85a9f8a0
05
spacevista
camera_angle
video_frame_sequence
Please estimate the overall rotation of the camera in the video, ignoring translation. Report the angle in degrees.
53 deg
Please estimate the overall rotation of the camera in the video, ignoring translation.
53
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。
32
[31]
spacevista:1000152
uco3d_toys_and_games_1180-52059-75280
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1000153}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 30]], "video_frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30...
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
fffac2d56eb053ff02f623ce5ef435192c8a31135ea89481db8e2f8e6988eebb
06
spacevista
camera_depth
video_frame_sequence
Provide the range to the object that the red box frames in the first video frame (in centimeters).
12.7 cm
Provide the range to the object that the red box frames in the first video frame (in centimeters).
12.7
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。
32
[32]
spacevista:1000004
wildrgbd_detergent_scene_102
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1000005}
{"semantic_modality": "video_frame_sequence", "frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]], "video_frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30...
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
bb7d42688bd943f0350a2c7c6b1181c5b74e64db9bbc6dcf2062c5a9184a4853
07
vsi590k
angle
video_file
These are frames of a video. At the door, facing the chair, what's the precise angle of clockwise rotation required to turn toward the trash bin? Please answer the question using a single word or phrase. Report the angle in degrees.
18 deg
<image> These are frames of a video. At the door, facing the chair, what's the precise angle of clockwise rotation required to turn toward the trash bin? Please answer the question using a single word or phrase.
18
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[1090]
vsi590k:10
scene0191_00
apache-2.0
346fbd4e41dec974bf24894d0541a49327ee6669
{"repo_id": "nyu-visionx/VSI-590K", "source_file": "vsi_590k.jsonl", "source_line": 11}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
2209f44b96280773cf73ef91d948b76bb66aae8f6e32e53c34cd075c50b19e70
08
vsi590k
area
video_file
These are frames of a video. Please indicate the size of the room using square feet. If there are multiple rooms, estimate the combined area. Please answer the question using a single word or phrase.
192 ft2
<image> These are frames of a video. Please indicate the size of the room using square feet. If there are multiple rooms, estimate the combined area. Please answer the question using a single word or phrase.
192
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[9775]
vsi590k:178066
56a0ec536c
apache-2.0
346fbd4e41dec974bf24894d0541a49327ee6669
{"repo_id": "nyu-visionx/VSI-590K", "source_file": "vsi_590k.jsonl", "source_line": 178067}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
6e09e349878244c3d9c0b685b99e91e9349ee20c569ec3edd7960cfaccde3ee1
09
vsi590k
closest_surface
video_file
These are frames of a video. Specify precisely how far apart the whiteboard and the telephone are at their closest points, expressed in centimeters. Please answer the question using a single word or phrase.
240 cm
<image> These are frames of a video. Specify precisely how far apart the whiteboard and the telephone are at their closest points, expressed in centimeters. Please answer the question using a single word or phrase.
240.0
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[9867]
vsi590k:155095
39f36da05b
apache-2.0
346fbd4e41dec974bf24894d0541a49327ee6669
{"repo_id": "nyu-visionx/VSI-590K", "source_file": "vsi_590k.jsonl", "source_line": 155096}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
215254faab567213aec16acc88efe172b65c5226042eb31109d806c2890e10f3
10
sims_vsi
area
video_file
These are frames of a video. What is the size of this room (in square meters)? If multiple rooms are shown, estimate the size of the combined space. Please answer the question using a single word or phrase.
263.7 m2
<image>These are frames of a video. What is the size of this room (in square meters)? If multiple rooms are shown, estimate the size of the combined space. Please answer the question using a single word or phrase.
263.7
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[461]
sims_vsi:qas/vsi_room_size_est_oe_seed_0.jsonl:0
sims_vsi:000345
apache-2.0
ba9439fdd50be43483f0541fd2d3341adbeb8a1a
{"repo_id": "ellisbrown/SIMS-VSI", "source_file": "qas/vsi_room_size_est_oe_seed_0.jsonl", "source_line": 1}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
ce588e4aa7a559966d6b51b807a6836a0e0b7be360f3de71e6d29fb1685a7627
11
sims_vsi
longest_side
video_file
These are frames of a video. What is the length of the longest dimension (length, width, or height) of the painting, measured in centimeters? Please answer the question using a single word or phrase.
80 cm
<image>These are frames of a video. What is the length of the longest dimension (length, width, or height) of the painting, measured in centimeters? Please answer the question using a single word or phrase.
80
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[800]
sims_vsi:qas/vsi_obj_size_est_oe_seed_0.jsonl:0
sims_vsi:001049
apache-2.0
ba9439fdd50be43483f0541fd2d3341adbeb8a1a
{"repo_id": "ellisbrown/SIMS-VSI", "source_file": "qas/vsi_obj_size_est_oe_seed_0.jsonl", "source_line": 1}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
8d9275f2a1242bbcb2c0a8ab5b56a8bafc945ab776ef6c6b5f3c13f453d8ab24
12
sims_vsi
surface_distance
video_file
These are frames of a video. Measuring from the closest point of each object, what is the direct distance between the clothes dryer and the handcart (in meters)? Please answer the question using a single word or phrase.
8.3 m
<image>These are frames of a video. Measuring from the closest point of each object, what is the direct distance between the clothes dryer and the handcart (in meters)? Please answer the question using a single word or phrase.
8.3
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[337]
sims_vsi:qas/vsi_obj_abs_distance_oe_seed_0.jsonl:10
sims_vsi:001457
apache-2.0
ba9439fdd50be43483f0541fd2d3341adbeb8a1a
{"repo_id": "ellisbrown/SIMS-VSI", "source_file": "qas/vsi_obj_abs_distance_oe_seed_0.jsonl", "source_line": 11}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
1a8ec9508a5426aa521c9d602b8610b1864d569e53eb21f590baf138208331c5
13
vica322k
area
video_file
Determine the total area of this room in square meters. If multiple rooms are present, estimate the combined space.
12.72 m2
<image> Determine the total area of this room in square meters. If multiple rooms are present, estimate the combined space.
12.72
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[57]
vica322k:arkitscenes/base/room_size.json:0
arkitscenes:40753679
cc-by-nc-4.0
2c443f51bbf401763972cb32b962aeb843ce56c1
{"repo_id": "nkkbr/ViCA-322K", "source_file": "arkitscenes/base/room_size.json", "source_line": 1}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
59070bbd63e56477ee5aa3b7348c63a724584922121f60d46cbd4622b3c6f305
14
vica322k
longest_side
video_file
How long is the largest side (length, width, or height) of the sink in centimeters?
78 cm
<image> How long is the largest side (length, width, or height) of the sink in centimeters?
78
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[47]
vica322k:arkitscenes/base/object_size_estimation.json:0
arkitscenes:48018776
cc-by-nc-4.0
2c443f51bbf401763972cb32b962aeb843ce56c1
{"repo_id": "nkkbr/ViCA-322K", "source_file": "arkitscenes/base/object_size_estimation.json", "source_line": 1}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
f1d684f7602db64f1805ba31559a46ed5df31743e67a3e395b024ba5cac04204
15
vica322k
surface_distance
video_file
How many meters apart are the closest points of sink and toilet?
1.7 m
<image> How many meters apart are the closest points of sink and toilet?
1.7
MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。
16
[63]
vica322k:arkitscenes/base/object_abs_distance.json:1
arkitscenes:48018778
cc-by-nc-4.0
2c443f51bbf401763972cb32b962aeb843ce56c1
{"repo_id": "nkkbr/ViCA-322K", "source_file": "arkitscenes/base/object_abs_distance.json", "source_line": 2}
{"semantic_modality": "video_file", "frame_groups": [], "video_frame_groups": [], "modality_evidence": "video_container", "timing_available": true}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
bed61844f649f298c143ba93135c97aea469701921e484ce7d198035527bb692
16
spacevista
area
multi_image_unresolved
From the video, calculate the approximate total size of the room in square meters. Your input must be limited to a single number. Please give your final answer between the <answer> </answer> tags.
<answer>10 m2</answer>
From the video, calculate the approximate total size of the room in square meters. Your input must be limited to a single number. Please give your final answer between the <answer> </answer> tags.
10
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。
16
[16]
spacevista:1001459
scene0429_00_10_1_0
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1001460}
{"semantic_modality": "multi_image_unresolved", "frame_groups": [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]], "video_frame_groups": [], "modality_evidence": "source_groups_preserved_temporal_provenance_unverified", "timing_available": false, "source_sequence_count": 1, "original_frame_occurrences": 16}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
a0945a4f43ebd0e741298aa396b4f9d21c5efdc25c9d3e5a0704a35b9b8a9919
17
spacevista
camera_depth
multi_image_unresolved
If the center of the paper towel roll (red point) is 1.5 meters deep, what is the depth of trash bin (blue point)? Calculate or judge based on the 3D center points of these objects. Input a single number to complete your answer. Please give your final answer between the <answer> </answer> tags.
<answer>1.2 m</answer>
If the center of the paper towel roll (red point) is 1.5 meters deep, what is the depth of trash bin (blue point)? Calculate or judge based on the 3D center points of these objects. Input a single number to complete your answer. Please give your final answer between the <answer> </answer> tags.
1.2
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。
3
[3]
spacevista:1155590
scene0492_01_2205_0
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1155591}
{"semantic_modality": "multi_image_unresolved", "frame_groups": [[0, 1, 2]], "video_frame_groups": [], "modality_evidence": "source_groups_preserved_temporal_provenance_unverified", "timing_available": false, "source_sequence_count": 1, "original_frame_occurrences": 3}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
3ffdc21c64c6a8e6c1f2daae0949b3aaf1d175e178f19d0836f26d0dbec71169
18
spacevista
center_depth
multi_image_unresolved
The depth of sofa chair (red point) is given as 3.1. Calculate how far apart in depth table (green point) and column (blue point) are from each other in meters. Calculate or judge based on the 3D center points of these objects. The depth is calculated based on the image where the markers corresponding to these objects ...
<answer>0.5</answer>
The depth of sofa chair (red point) is given as 3.1. Calculate how far apart in depth table (green point) and column (blue point) are from each other in meters. Calculate or judge based on the 3D center points of these objects. The depth is calculated based on the image where the markers corresponding to these objects ...
0.5
全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。
3
[3]
spacevista:1000201
1140
cc-by-4.0
0c0c9b41654087f8ad3c680fc8786b4cab6191dc
{"repo_id": "SpaceVista/SpaceVista-Full", "source_file": "all.json", "source_line": 1000202}
{"semantic_modality": "multi_image_unresolved", "frame_groups": [[0, 1, 2]], "video_frame_groups": [], "modality_evidence": "source_groups_preserved_temporal_provenance_unverified", "timing_available": false, "source_sequence_count": 1, "original_frame_occurrences": 3}
AnchorSR/TrainingData_Stage3
a6cb55497a991b327b32410d946e41d3bf0f3610
small/train
4b187361b884214d72404a9a2cdd7957e672cac16d837c6d15eaeefdbcf3ffdb

Stage3 视频/多图人工查看样例

这是 18条人工查看样例,不是新训练集或评测集。直接向下浏览 QA 和拼图, 也可在 Dataset Viewer 中查看 frames 图片列。训练 QA 与原数据逐字保留;答案是数据集标注,不是人工确认的视觉真值。

来源 已确认视频类 待判断多图
CA-VQA 3(有序帧) 0
SpaceVista 3(有序帧) 3
VSI-590K 3(视频文件) 0
SIMS-VSI 3(视频文件) 0
ViCA-322K 3(视频文件) 0

选样:从正式 Small/train 中按固定 ID 顺序选择,优先不同任务、不同来源场景;不是随机代表性统计,也没有按答案是否正确挑样。 每张拼图从左到右、从上到下阅读。视频文件全程均匀抽取最多16帧;帧序列保留全部输入帧。 展示缩放不改变正式训练数据;拼图不是模型训练输入。多图未知项不计为视频。

来源:AnchorSR/TrainingData_Stage3, 固定提交 a6cb55497a991b327b32410d946e41d3bf0f3610,Small/train(同时属于 Large)。 每条提供 sample_id、来源版本、场景、原始 QA、实际训练 QA 与输入分组。

许可沿用原始数据,此仓库不重新授权:CA-VQA/CubifyAnything 为 CC-BY-NC-ND-4.0; SpaceVista 为 CC-BY-4.0;VSI-590K、SIMS-VSI 为 Apache-2.0;ViCA-322K 为 CC-BY-NC-4.0。 上游媒体自身的许可条件仍适用。不得将混合集视为可自由商用或重新许可的素材。 本仓库仅供检查;需遵守源数据对使用、修改和再分发的限制。

01 · cavqa · camera_depth

模态:video_frame_sequence;许可:cc-by-nc-nd-4.0。

Q(训练输入)

How far away is the painting?

A(训练答案)

1.48 m

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。

01 frames

原始 QA 与样例 ID
{
  "question": "How far away is the painting?",
  "raw_answer": "1.48m"
}

cavqa:00000-of-01024:100:99

02 · cavqa · height

模态:video_frame_sequence;许可:cc-by-nc-nd-4.0。

Q(训练输入)

How tall is the book?

A(训练答案)

9 cm

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。

02 frames

原始 QA 与样例 ID
{
  "question": "How tall is the book?",
  "raw_answer": "9cm"
}

cavqa:00000-of-01024:102:28

03 · cavqa · length

模态:video_frame_sequence;许可:cc-by-nc-nd-4.0。

Q(训练输入)

What is the length of vacuum cleaner?

A(训练答案)

32 cm

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 REF是末尾参考帧:前面的支持帧加参考帧不应理解为严格连续播放的视频。

03 frames

原始 QA 与样例 ID
{
  "question": "What is the length of vacuum cleaner?",
  "raw_answer": "32cm"
}

cavqa:00000-of-01024:111:20

04 · spacevista · area

模态:video_frame_sequence;许可:cc-by-4.0。

Q(训练输入)

Estimate the floor space of the room visible in the footage (in square meters).

A(训练答案)

20 m2

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。

04 frames

原始 QA 与样例 ID
{
  "question": "Estimate the floor space of the room visible in the footage (in square meters).",
  "raw_answer": "20"
}

spacevista:1001419

05 · spacevista · camera_angle

模态:video_frame_sequence;许可:cc-by-4.0。

Q(训练输入)

Please estimate the overall rotation of the camera in the video, ignoring translation.
Report the angle in degrees.

A(训练答案)

53 deg

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。

05 frames

原始 QA 与样例 ID
{
  "question": "Please estimate the overall rotation of the camera in the video, ignoring translation.",
  "raw_answer": "53"
}

spacevista:1000152

06 · spacevista · camera_depth

模态:video_frame_sequence;许可:cc-by-4.0。

Q(训练输入)

Provide the range to the object that the red box frames in the first video frame (in centimeters).

A(训练答案)

12.7 cm

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。

06 frames

原始 QA 与样例 ID
{
  "question": "Provide the range to the object that the red box frames in the first video frame (in centimeters).",
  "raw_answer": "12.7"
}

spacevista:1000004

07 · vsi590k · angle

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
At the door, facing the chair, what's the precise angle of clockwise rotation required to turn toward the trash bin?
Please answer the question using a single word or phrase.
Report the angle in degrees.

A(训练答案)

18 deg

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

07 frames

原始 QA 与样例 ID
{
  "question": "<image>\nThese are frames of a video.\nAt the door, facing the chair, what's the precise angle of clockwise rotation required to turn toward the trash bin?\nPlease answer the question using a single word or phrase.",
  "raw_answer": "18"
}

vsi590k:10

08 · vsi590k · area

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
Please indicate the size of the room using square feet. If there are multiple rooms, estimate the combined area.
Please answer the question using a single word or phrase.

A(训练答案)

192 ft2

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

08 frames

原始 QA 与样例 ID
{
  "question": "<image>\nThese are frames of a video.\nPlease indicate the size of the room using square feet. If there are multiple rooms, estimate the combined area.\nPlease answer the question using a single word or phrase.",
  "raw_answer": "192"
}

vsi590k:178066

09 · vsi590k · closest_surface

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
Specify precisely how far apart the whiteboard and the telephone are at their closest points, expressed in centimeters.
Please answer the question using a single word or phrase.

A(训练答案)

240 cm

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

09 frames

原始 QA 与样例 ID
{
  "question": "<image>\nThese are frames of a video.\nSpecify precisely how far apart the whiteboard and the telephone are at their closest points, expressed in centimeters.\nPlease answer the question using a single word or phrase.",
  "raw_answer": "240.0"
}

vsi590k:155095

10 · sims_vsi · area

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
What is the size of this room (in square meters)?
If multiple rooms are shown, estimate the size of the combined space.
Please answer the question using a single word or phrase.

A(训练答案)

263.7 m2

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

10 frames

原始 QA 与样例 ID
{
  "question": "<image>These are frames of a video.\nWhat is the size of this room (in square meters)?\nIf multiple rooms are shown, estimate the size of the combined space.\nPlease answer the question using a single word or phrase.",
  "raw_answer": "263.7"
}

sims_vsi:qas/vsi_room_size_est_oe_seed_0.jsonl:0

11 · sims_vsi · longest_side

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
What is the length of the longest dimension (length, width, or height) of the painting, measured in centimeters?
Please answer the question using a single word or phrase.

A(训练答案)

80 cm

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

11 frames

原始 QA 与样例 ID
{
  "question": "<image>These are frames of a video.\nWhat is the length of the longest dimension (length, width, or height) of the painting, measured in centimeters?\nPlease answer the question using a single word or phrase.",
  "raw_answer": "80"
}

sims_vsi:qas/vsi_obj_size_est_oe_seed_0.jsonl:0

12 · sims_vsi · surface_distance

模态:video_file;许可:apache-2.0。

Q(训练输入)

These are frames of a video.
Measuring from the closest point of each object, what is the direct distance between the clothes dryer and the handcart (in meters)?
Please answer the question using a single word or phrase.

A(训练答案)

8.3 m

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

12 frames

原始 QA 与样例 ID
{
  "question": "<image>These are frames of a video.\nMeasuring from the closest point of each object, what is the direct distance between the clothes dryer and the handcart (in meters)?\nPlease answer the question using a single word or phrase.",
  "raw_answer": "8.3"
}

sims_vsi:qas/vsi_obj_abs_distance_oe_seed_0.jsonl:10

13 · vica322k · area

模态:video_file;许可:cc-by-nc-4.0。

Q(训练输入)

Determine the total area of this room in square meters. If multiple rooms are present, estimate the combined space.

A(训练答案)

12.72 m2

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

13 frames

原始 QA 与样例 ID
{
  "question": "<image>\nDetermine the total area of this room in square meters. If multiple rooms are present, estimate the combined space.",
  "raw_answer": "12.72"
}

vica322k:arkitscenes/base/room_size.json:0

14 · vica322k · longest_side

模态:video_file;许可:cc-by-nc-4.0。

Q(训练输入)

How long is the largest side (length, width, or height) of the sink in centimeters?

A(训练答案)

78 cm

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

14 frames

原始 QA 与样例 ID
{
  "question": "<image>\nHow long is the largest side (length, width, or height) of the sink in centimeters?",
  "raw_answer": "78"
}

vica322k:arkitscenes/base/object_size_estimation.json:0

15 · vica322k · surface_distance

模态:video_file;许可:cc-by-nc-4.0。

Q(训练输入)

How many meters apart are the closest points of sink and toilet?

A(训练答案)

1.7 m

MP4 视频按完整解码帧范围均匀抽取最多16帧;仅用于展示,不代表训练抽帧策略。帧号从0开始。

15 frames

原始 QA 与样例 ID
{
  "question": "<image>\nHow many meters apart are the closest points of sink and toilet?",
  "raw_answer": "1.7"
}

vica322k:arkitscenes/base/object_abs_distance.json:1

16 · spacevista · area

模态:multi_image_unresolved;许可:cc-by-4.0。

Q(训练输入)

From the video, calculate the approximate total size of the room in square meters. Your input must be limited to a single number.
Please give your final answer between the <answer> </answer> tags.

A(训练答案)

<answer>10 m2</answer>

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。

16 frames

原始 QA 与样例 ID
{
  "question": "From the video, calculate the approximate total size of the room in square meters. Your input must be limited to a single number.\nPlease give your final answer between the <answer> </answer> tags.",
  "raw_answer": "10"
}

spacevista:1001459

17 · spacevista · camera_depth

模态:multi_image_unresolved;许可:cc-by-4.0。

Q(训练输入)

If the center of the paper towel roll (red point) is 1.5 meters deep, what is the depth of trash bin (blue point)?  Calculate or judge based on the 3D center points of these objects. Input a single number to complete your answer.
Please give your final answer between the <answer> </answer> tags.

A(训练答案)

<answer>1.2 m</answer>

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。

17 frames

原始 QA 与样例 ID
{
  "question": "If the center of the paper towel roll (red point) is 1.5 meters deep, what is the depth of trash bin (blue point)?  Calculate or judge based on the 3D center points of these objects. Input a single number to complete your answer.\nPlease give your final answer between the <answer> </answer> tags.",
  "raw_answer": "1.2"
}

spacevista:1155590

18 · spacevista · center_depth

模态:multi_image_unresolved;许可:cc-by-4.0。

Q(训练输入)

The depth of sofa chair (red point) is given as 3.1. Calculate how far apart in depth table (green point) and column (blue point) are from each other in meters. Calculate or judge based on the 3D center points of these objects. The depth is calculated based on the image where the markers corresponding to these objects are located.
Provide your reasoning in <think> </think>.
Provide only the numerical value (e.g., 42 or 3.14) in meters in <answer> </answer>.

A(训练答案)

<answer>0.5</answer>

全部输入图片按原分组和顺序展示,保留重复帧及读取器渲染的框/点/掩码;G表示源分组,input编号从1开始,不是原视频帧号。 此例尚不能确认时间顺序或视频属性,请人工判断。

18 frames

原始 QA 与样例 ID
{
  "question": "The depth of sofa chair (red point) is given as 3.1. Calculate how far apart in depth table (green point) and column (blue point) are from each other in meters. Calculate or judge based on the 3D center points of these objects. The depth is calculated based on the image where the markers corresponding to these objects are located.\nProvide your reasoning in <think> </think>.\nProvide only the numerical value (e.g., 42 or 3.14) in meters in <answer> </answer>.",
  "raw_answer": "0.5"
}

spacevista:1000201

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