Deep Fakes Dataset (inamibora)
Introduced by Ciftci et al. in FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals
The Deep Fakes Dataset is a collection of "in the wild" portrait videos for deepfake detection. The videos in the dataset are diverse real-world samples in terms of the source generative model, resolution, compression, illumination, aspect-ratio, frame rate, motion, pose, cosmetics, occlusion, content, and context. They originate from various sources such as news articles, forums, apps, and research presentations; totalling up to 142 videos, 32 minutes, and 17 GBs. Synthetic videos are matched with their original counterparts when possible.
Source: Deepfakes datasetPapers
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