video_id stringclasses 6
values | split stringclasses 1
value | source_split stringclasses 1
value | source_dataset stringclasses 1
value | category stringclasses 6
values | youtube_url stringclasses 6
values | clip_reference stringclasses 6
values | clip_start_seconds int64 3 1.91k | clip_end_seconds int64 13 1.92k | fps float64 15 30 | duration_seconds float64 9.43 10 | num_frames int64 150 300 | annotator_count int64 3 5 | selected_annotator_index int64 0 0 | selected_annotator_consistency float64 1 1 | mean_annotator_consistency float64 1 1 | boundaries listlengths 1 15 | annotation_license stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0x8ux7SrwZE | train | train | Kinetics-GEBD | trimming_or_shaving_beard | https://www.youtube.com/watch?v=0x8ux7SrwZE | trimming_or_shaving_beard/0x8ux7SrwZE_000061_000071.mp4 | 61 | 71 | 30 | 9.433333 | 283 | 5 | 0 | 1 | 1 | [
{
"start_seconds": 1.49866,
"end_seconds": 1.69986,
"boundary_kind": "visual_change",
"change_type": "Change due to Fade/Dissolve/Gradual"
}
] | CC-BY-NC-4.0 |
150momul7So | train | train | Kinetics-GEBD | surfing_crowd | https://www.youtube.com/watch?v=150momul7So | surfing_crowd/150momul7So_000004_000014.mp4 | 4 | 14 | 15 | 10 | 150 | 4 | 0 | 1 | 1 | [
{
"start_seconds": 0,
"end_seconds": 1.51441,
"boundary_kind": "visual_change",
"change_type": "Change due to Pan"
}
] | CC-BY-NC-4.0 |
1N6ACNX3pwg | train | train | Kinetics-GEBD | parasailing | https://www.youtube.com/watch?v=1N6ACNX3pwg | parasailing/1N6ACNX3pwg_000006_000016.mp4 | 6 | 16 | 25 | 10 | 250 | 5 | 0 | 1 | 1 | [
{
"start_seconds": 0.58538,
"end_seconds": 0.58538,
"boundary_kind": "visual_change",
"change_type": "Change due to Cut"
},
{
"start_seconds": 1.28111,
"end_seconds": 1.28111,
"boundary_kind": "visual_change",
"change_type": "Change due to Cut"
},
{
"start_seconds": 1.805... | CC-BY-NC-4.0 |
2BT8CiKHdTI | train | train | Kinetics-GEBD | mowing_lawn | https://www.youtube.com/watch?v=2BT8CiKHdTI | mowing_lawn/2BT8CiKHdTI_000003_000013.mp4 | 3 | 13 | 29.97003 | 10.01 | 300 | 3 | 0 | 1 | 1 | [
{
"start_seconds": 0.76771,
"end_seconds": 0.76771,
"boundary_kind": "semantic_event",
"change_type": "Change of Actor/Subject"
},
{
"start_seconds": 1.81063,
"end_seconds": 1.81063,
"boundary_kind": "semantic_event",
"change_type": "Change of Actor/Subject"
},
{
"start_s... | CC-BY-NC-4.0 |
2pg0JFkEZQg | train | train | Kinetics-GEBD | cheerleading | https://www.youtube.com/watch?v=2pg0JFkEZQg | cheerleading/2pg0JFkEZQg_000061_000071.mp4 | 61 | 71 | 29.916667 | 10.027855 | 300 | 5 | 0 | 1 | 1 | [
{
"start_seconds": 1.55957,
"end_seconds": 2.07543,
"boundary_kind": "visual_change",
"change_type": "Change due to Fade/Dissolve/Gradual"
},
{
"start_seconds": 5.08659,
"end_seconds": 5.61445,
"boundary_kind": "visual_change",
"change_type": "Change due to Fade/Dissolve/Gradual"... | CC-BY-NC-4.0 |
44cW2Z6AVHo | train | train | Kinetics-GEBD | yoga | https://www.youtube.com/watch?v=44cW2Z6AVHo | yoga/44cW2Z6AVHo_001911_001921.mp4 | 1,911 | 1,921 | 30 | 10 | 300 | 5 | 0 | 1 | 1 | [
{
"start_seconds": 3.68417,
"end_seconds": 3.68417,
"boundary_kind": "visual_change",
"change_type": "Change due to Cut"
}
] | CC-BY-NC-4.0 |
Streaming GEBD Causal Preview
Ten metadata-only examples derived from the official Kinetics-GEBD raw annotations. This preview validates the schema intended for causal streaming event-boundary training before publishing a full processed release.
Splits
train: 6 examples from the original Kinetics-GEBD training annotations.validation: 2 examples from the original validation annotations.test: 2 held-out examples from the original validation annotations.
The selected annotation for each clip is the annotation from the annotator with the highest consistency score. The complete release may replace this preview policy with consensus boundary aggregation.
Video access
This repository does not redistribute Kinetics YouTube videos. Each row contains the YouTube ID, source URL, and the original Kinetics clip start/end seconds. Availability and usage rights of each source video remain subject to YouTube and the original uploader.
Causal use
At time t, a streaming model must receive only frames with timestamps less
than or equal to t. It must not use frames after the candidate boundary.
boundary_kind separates:
semantic_event: actor, object, action, or other semantic state change.visual_change: cut, pan, zoom, fade, or speed transition.
Sources and license
Annotations are derived from StanLei52/GEBD, licensed under CC BY-NC 4.0. Cite:
@inproceedings{shou2021gebd,
title={Generic Event Boundary Detection: A Benchmark for Event Segmentation},
author={Shou, Mike Zheng and Lei, Stan Weixian and Wang, Weiyao and Ghadiyaram, Deepti and Feiszli, Matt},
booktitle={ICCV},
year={2021}
}
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