JamalLee/

Omni-Fake-OOD

Omni-Fake-OOD is the out-of-distribution benchmark split of Omni-Fake. Samples come from held-out generators and platforms not included in training, for measuring cross-domain generalization. It covers image, audio, video, and audio–video talking-head (AV-TH) with the same three-class labels as Omni-Fake-SET: real, fully synthetic, and tampered. Use together with Omni-Fake-SET (in-distribution training data).

Paper: arXiv:2605.01638 Project page: Omni-Fake… See the full description on the dataset page: https://huggingface.co/datasets/JamalLee/Omni-Fake-OOD.