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"The screen shows the title of preparing a Chilean Hulte salad dish.",
" A person is mixing salad ingredients in a large bowl.",
" There is information shown about Dr.",
" Rachel Collin's trip to Chile.",
" There are several people standing under a canopy at a food market.",
" Two customers make a purchase and give money to the seller and give the camera a thumbs up.",
" The chef is showing hulte placed on a kitchen counter.",
" The chef is slicing the hulte in circular bite size pieces.",
" A woman eats the cut pieces of hulte.",
" The chef chops some cilantro on the kitchen counter.",
" Then the chef places the ingredients in a salad bowl.",
" The finished product is shown on screen, followed by a group of people sitting together and enjoying the salad.",
" The end credits are displayed on the screen."
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"A man is shown standing in front of a blue background as many harmonicas are shown and he starts playing them.",
" He is then shown speaking into the camera and going into detail with regards to the products features.",
" He shows off how many he has in his coat and continues talking.",
" He is then shown playing another harmonica as he gives instruction on it.",
" He speaks some more and shows his harmonica again as the video goes to an end title screen that reads Howcast original\"."
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"One man is then shown and he bends down and shows the proper way to lift the bar with weight on it.",
"A replay is then shown and the boy bends from the knees and then flips his wrist and brings it over his shoulder as he goes down into a squatting position."
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" The man rides a wave, then through it.",
" He completes several stunts before walking onto the beach with the board under his arm."
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[
[
21.02,
33.38
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[
24.1,
28.87
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[
21.33,
30.9
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[
20.74,
27
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[
19.09,
29.45
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[
21.62,
29.78
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[
20.2,
24.5
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[
16.76,
22.52
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[
20.26,
23.71
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[
25.36,
33.68
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[
[
89.65,
105.32
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[
106.65,
123.07
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[
119.57,
132.73
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[
57.6,
68.12
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43.67,
60.2
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[
54.63,
72.22
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51.07,
60.96
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45.25,
55.28
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[
46.93,
63.26
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[
63.39,
78.48
]
],
[
[
186.29,
198.9
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[
159.7,
175.41
],
[
174.57,
189.46
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[
120.37,
138.71
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[
101.59,
111.9
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[
198.09,
208.43
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[
120.71,
141.95
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[
134.9,
155.34
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[
97.87,
119.98
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[
161.05,
174.26
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]
] | [
"A man is shown flipping a violin in his hands, playing a popular song on his violin.",
" The camera shows the violinist from various angles playing the popular song and not breaking concentration.",
" The camera pans all around the player and shows him playing the complete song."
] | v_9rW35YTKYq8 |
End of preview. Expand
in Dataset Viewer.
Dataset Card for VideoXum
Dataset Summary
The VideoXum dataset represents a novel task in the field of video summarization, extending the scope from single-modal to cross-modal video summarization. This new task focuses on creating video summaries that containing both visual and textual elements with semantic coherence. Built upon the foundation of ActivityNet Captions, VideoXum is a large-scale dataset, including over 14,000 long-duration and open-domain videos. Each video is paired with 10 corresponding video summaries, amounting to a total of 140,000 video-text summary pairs.
Languages
The textual summarization in the dataset are in English.
Dataset Structure
Dataset Splits
train | validation | test | Overall | |
---|---|---|---|---|
# of videos | 8,000 | 2,001 | 4,000 | 14,001 |
Dataset Resources
train_videoxum.json
: annotations of training setval_videoxum.json
: annotations of validation settest_videoxum.json
: annotations of test set
Dataset Fields
video_id
:str
a unique identifier for the video.duration
:float
total duration of the video in seconds.sampled_frames
:int
the number of frames sampled from source video at 1 fps with a uniform sampling schema.timestamps
:List_float
a list of timestamp pairs, with each pair representing the start and end times of a segment within the video.tsum
:List_str
each textual video summary provides a summarization of the corresponding video segment as defined by the timestamps.vsum
:List_float
each visual video summary corresponds to key frames within each video segment as defined by the timestamps. The dimensions (3 x 10) suggest that each video segment was reannotated by 10 different workers.vsum_onehot
:List_bool
one-hot matrix transformed from 'vsum'. The dimensions (10 x 83) denotes the one-hot labels spanning the entire length of a video, as annotated by 10 workers.
Annotation Sample
For each video, We hire workers to annotate ten shortened video summaries.
{
'video_id': 'v_QOlSCBRmfWY',
'duration': 82.73,
'sampled_frames': 83
'timestamps': [[0.83, 19.86], [17.37, 60.81], [56.26, 79.42]],
'tsum': ['A young woman is seen standing in a room and leads into her dancing.',
'The girl dances around the room while the camera captures her movements.',
'She continues dancing around the room and ends by laying on the floor.'],
'vsum': [[[ 7.01, 12.37], ...],
[[41.05, 45.04], ...],
[[65.74, 69.28], ...]] (3 x 10 dim)
'vsum_onehot': [[[0,0,0,...,1,1,...], ...],
[[0,0,0,...,1,1,...], ...],
[[0,0,0,...,1,1,...], ...],] (10 x 83 dim)
}
File Structure of Dataset
The file structure of VideoXum looks like:
dataset
βββ ActivityNet
βββ anno
β βββ test_videoxum.json
β βββ train_videoxum.json
β βββ val_videoxum.json
βββ feat
βββ blip
β βββ v_00Dk03Jr70M.npz
β βββ ...
βββ vt_clipscore
βββ v_00Dk03Jr70M.npz
βββ ...
Citation
@article{lin2023videoxum,
author = {Lin, Jingyang and Hua, Hang and Chen, Ming and Li, Yikang and Hsiao, Jenhao and Ho, Chiuman and Luo, Jiebo},
title = {VideoXum: Cross-modal Visual and Textural Summarization of Videos},
journal = {IEEE Transactions on Multimedia},
year = {2023},
}
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