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End of preview. Expand in Data Studio
Audited Kinetics-GEBD Causal Metadata
This metadata-only release converts the publicly released Kinetics-GEBD annotations into an auditable 24 FPS causal training representation. It does not redistribute Kinetics or YouTube video bytes.
Splits
| Hub split | Official source file | Records | Meaning |
|---|---|---|---|
train |
k400_train_raw_annotation.pkl |
18,808 | Public GEBD training annotations |
validation |
k400_val_raw_annotation.pkl |
18,815 | Public Kinetics-GEBD validation annotations |
The ICCV 2021 benchmark describes a separate challenge test subset sampled
from Kinetics-400 train. Its labels are withheld and are not included here.
The ICCV 2025 On-GEBD paper explicitly evaluates Kinetics-GEBD on the public
validation split because test annotations are unavailable.
Annotation processing
The release reproduces the official
prepare_k400_release.ipynb
behavior, including its input-order and list-mutation quirks:
- discard boundaries in the first or last 0.3 seconds;
- merge overlapping gradual-shot ranges;
- suppress timestamp boundaries around gradual-shot ranges;
- suppress nearby same-type timestamps and prefer shots over events;
- convert cleaned timestamps to source-frame indices with
floor(timestamp * source_fps), capped atnum_frames - 1.
The implementation was differentially checked against the official notebook over all 185,518 released rater annotations with zero timestamp-sequence differences. This is intentionally the code behavior: some effective suppression distances are 0.6 seconds even though the paper summarizes a 0.1-second merge rule.
Training uses the first maximum of f1_consis, matching numpy.argmax in the
official loader. Evaluation must compare predictions independently with every
retained rater and select the best rater-specific F1. Records with
f1_consis_avg < 0.3 remain present but have evaluation_eligible=false.
Causal 24 FPS labels
The benchmark does not publish a canonical 24 FPS binary-label file. This release derives one for causal training:
sample_count = ceil(duration_seconds * 24);- sample
irepresents timestampi / 24; - a sample is positive when it falls inclusively within 0.15 seconds of a cleaned boundary from the highest-consistency training rater.
boundary_source_frame_indices and
training_boundary_source_frame_indices preserve official source-FPS frame
coordinates. training_boundary_sample_indices and binary_labels are the
derived 24 FPS projection. These fields must not be conflated.
Evaluation
The official metric is relative temporal distance, not the 0.15-second training window. The paper reports F1 at thresholds 0.05 through 0.50; the challenge ranking metric is F1@0.05. Matching is one-to-one and performed separately for each rater, retaining the rater yielding the best F1.
Videos
The local acquisition audit resolved and ffprobe-validated 37,608 of 37,623
referenced clips:
| Source split | Available | Missing |
|---|---|---|
| train | 18,794 | 14 |
| val | 18,814 | 1 |
The remaining 15 references were absent from all inspected public mirrors,
the official CVDF Kinetics-400 archives, and accessible original-video paths.
See VIDEO_ACQUISITION.md and manifests/ for exact
availability and missing-reference records.
uv run scripts/build_official_on_gebd_dataset.py
uv run scripts/acquire_official_gebd_videos.py --workers 4
Rights
The GEBD annotation release is CC BY-NC 4.0 and the official repository code is MIT-licensed. Neither license grants redistribution rights for the underlying Kinetics/YouTube videos. A gated or private Hub repository does not change those rights, so this release contains metadata and manifests only.
Sources
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