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Omni-Fake-SET
Omni-Fake-SET is the in-distribution split of Omni-Fake, a unified multimodal deepfake dataset for social-media forensics. It covers image, audio, video, and audio–video talking-head (AV-TH) modalities. Each modality uses the same three-way label space: real, fully synthetic, and tampered. Pair with the held-out benchmark Omni-Fake-OOD for out-of-distribution evaluation.
- Paper: arXiv:2605.01638
- Project page: Omni-Fake
- License: CC-BY-4.0
Video (hybrid release)
SET Video totals 260,000 clips: 100,000 real + 100,000 full_synthetic + 60,000 tampered.
| Component | Count | Format on HF | Source |
|---|---|---|---|
| Real + Full_Synthetic | 200,000 | data/Video/video-set.7z.* (27 parts, ~114 GB) |
GenBuster-200K train split |
| Tampered | 60,000 | data/Video/train-*.parquet |
Omni-Fake PartialEdit |
Real / full_synthetic paths after extracting the .7z shards: train/real/ → real; train/fake/<generator>/ → full_synthetic (easyanimate, cogvideox, ltxvideo, hunyuanvideo). Tampered parquet rows use label=tampered, generator=PartialEdit.
Attribution: Real and full_synthetic video clips are from GenBuster-200K (MIT). Cite BusterX (arXiv:2505.12620) when using those clips.
Quick start
from datasets import load_dataset
# Image (default config)
ds_img = load_dataset("JamalLee/Omni-Fake-SET", "image")
print(ds_img)
# Audio
ds_aud = load_dataset("JamalLee/Omni-Fake-SET", "audio")
# Video tampered (parquet; Dataset Viewer)
ds_vid = load_dataset("JamalLee/Omni-Fake-SET", "video")
# Real + full_synthetic: download/extract data/Video/video-set.7z.*
# Audio–video talking head
ds_avth = load_dataset("JamalLee/Omni-Fake-SET", "avth")
Fields (by modality)
Image: image, mask, label, generator, filename, split
Audio: audio, label, generator, filename, split, spoof_intervals
Video (parquet, tampered only): video, label, generator, filename, split
Video (.7z, real + full_synthetic): extract video-set.7z.*; map train/real/ → real, train/fake/<generator>/ → full_synthetic
AV-TH: video, label, generator, filename, split
Labels are real, full_synthetic, or tampered (same three-class scheme for Image and Video).
Dataset Viewer
Open the Dataset Viewer tab and keep subset image selected (default). Subset video previews tampered parquet. Real and full_synthetic video require downloading the .7z archive.
Citation
@article{li2026omnifake,
title={Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection},
author={Li, Tianxiao and Huang, Zhenglin and Wen, Haiquan and others},
journal={arXiv preprint arXiv:2605.01638},
year={2026}
}
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