{"url":"/dataset/fakeavceleb","name":"FakeAVCeleb","full_name":null,"description_markdown":"FakeAVCeleb is a novel Audio-Video Deepfake dataset that not only contains deepfake videos but respective synthesized cloned audios as well. \r\n\r\nImage source: [https://arxiv.org/pdf/2108.05080v1.pdf](https://arxiv.org/pdf/2108.05080v1.pdf)","description_withheld":null,"homepage":"https://github.com/hasam6400/fakevaceleb","introduced_date":"2021-08-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/fakeavceleb-a-novel-audio-video-multimodal","title":"FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset","first_author":"Hasam Khalid","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"DeepFake Detection","url":"/task/deepfake-detection","datasets_with_task":"/datasets/task/deepfake-detection"},{"name":"Multimodal Forgery Detection","url":"/task/multimodal-forgery-detection","datasets_with_task":"/datasets/task/multimodal-forgery-detection"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["FakeAVCeleb"],"data_loaders":[{"repo":"https://github.com/bilgial/deepfake","url":"https://github.com/bilgial/deepfake","frameworks":["tf"]}],"num_papers_in_archive":65,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/deepfake-detection-on-fakeavceleb-1","task":"DeepFake Detection","dataset_variant":"FakeAVCeleb","rows":13,"metrics":["ROC AUC","AP","Accuracy (%)"],"first_row_in_archive_order":{"model":"FACTOR","paper":"/paper/detecting-deepfakes-without-seeing-any","metrics":{"AP":"96.8","ROC AUC":"97.4"},"code_links":[{"title":"talreiss/factor","url":"https://github.com/talreiss/factor"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multimodal-forgery-detection-on-fakeavceleb","task":"Multimodal Forgery Detection","dataset_variant":"FakeAVCeleb","rows":1,"metrics":["Accuracy (%)"],"first_row_in_archive_order":{"model":"Ensemble AudioVisual Model","paper":"/paper/multimodal-forgery-detection-using-ensemble","metrics":{"Accuracy (%)":"0.89"},"code_links":[{"title":"ammarahhashmi/Multimodal-Forgery-Detection-Using-Ensemble-Learning","url":"https://github.com/ammarahhashmi/Multimodal-Forgery-Detection-Using-Ensemble-Learning"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/av-lip-sync-leveraging-av-hubert-to-exploit","title":"AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection","date":"2023-11-05","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/detecting-deepfakes-without-seeing-any","title":"Detecting Deepfakes Without Seeing Any","date":"2023-11-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/avtenet-audio-visual-transformer-based","title":"AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection","date":"2023-10-19","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/self-supervised-video-forensics-by-audio","title":"Self-Supervised Video Forensics by Audio-Visual Anomaly Detection","date":"2023-01-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multimodal-forgery-detection-using-ensemble","title":"Multimodal Forgery Detection Using Ensemble Learning","date":"2022-11-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/lip-sync-matters-a-novel-multimodal-forgery","title":"Lip Sync Matters: A Novel Multimodal Forgery Detector","date":"2022-11-07","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/leveraging-real-talking-faces-via-self","title":"Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection","date":"2022-01-18","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/exploring-temporal-coherence-for-more-general","title":"Exploring Temporal Coherence for More General Video Face Forgery Detection","date":"2021-08-15","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":6,"samples_unverified":0,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/joint-audio-visual-deepfake-detection","title":"Joint Audio-Visual Deepfake Detection","date":"2021-01-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/taming-transformers-for-high-resolution-image","title":"Taming Transformers for High-Resolution Image Synthesis","date":"2020-12-17","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":6,"samples_unverified":0,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/lips-don-t-lie-a-generalisable-and-robust","title":"Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection","date":"2020-12-14","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/faceforensics-learning-to-detect-manipulated","title":"FaceForensics++: Learning to Detect Manipulated Facial Images","date":"2019-01-25","rows_on_this_dataset":1,"code_links":14,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":4,"samples_unverified":5,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":33,"samples_ran":17,"samples_unverified":16,"pointer_only_for_licence":14,"papers_with_no_sample_that_ran":2,"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."}