{"url":"/dataset/deep-fakes-dataset","name":"Deep Fakes Dataset","full_name":"inamibora","description_markdown":"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. \r\n\r\nSource: [Deepfakes dataset](http://cs.binghamton.edu/~ncilsal2/DeepFakesDataset/)","description_withheld":null,"homepage":"http://cs.binghamton.edu/~ncilsal2/DeepFakesDataset/","introduced_date":"2019-01-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/fakecatcher-detection-of-synthetic-portrait","title":"FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals","first_author":"Umur Aybars Ciftci","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Video Generation","url":"/task/video-generation","datasets_with_task":"/datasets/task/video-generation"},{"name":"Dimensionality Reduction","url":"/task/dimensionality-reduction","datasets_with_task":"/datasets/task/dimensionality-reduction"},{"name":"Video Compression","url":"/task/video-compression","datasets_with_task":"/datasets/task/video-compression"}],"languages":[],"variants":["Deep Fakes Dataset"],"data_loaders":[{"repo":"https://github.com/paarth2023/Dataset_for_hackathon","url":"https://github.com/paarth2023/Dataset_for_hackathon","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}