{"url":"/sota/deepfake-detection-on-dffd","task":{"name":"DeepFake Detection","url":"/task/deepfake-detection","note":null},"dataset":{"name":"DFFD","url":null},"category":"Computer Vision","categories":["Audio","Computer Vision","Miscellaneous","Speech"],"category_note":null,"description":"**DeepFake Detection** is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. The goal of deepfake detection is to identify such manipulations and distinguish them from real videos or images.\r\n\r\nDescription source: [DeepFakes: a New Threat to Face Recognition? Assessment and Detection](https://arxiv.org/pdf/1812.08685.pdf)\r\n\r\nImage source: [DeepFakes: a New Threat to Face Recognition? Assessment and Detection](https://paperswithcode.com/paper/deepfakes-a-new-threat-to-face-recognition)","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["AUC","Accuracy"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"AUC":"higher","Accuracy":"higher"}},"counts":{"rows":1,"rows_with_code":1,"rows_with_paper_page":1,"rows_dated":1,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"FasterThanLies","metrics":{"AUC":"0.9994","Accuracy":"0.9895"},"uses_additional_data":false,"paper_date":"2024-06-07","paper":"/paper/faster-than-lies-real-time-deepfake-detection","paper_url":"https://arxiv.org/abs/2406.04932v1","paper_title":"Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks","code":"https://github.com/fedeloper/binary_deepfake_detection","n_code_links":1,"syntology":null}],"since_archive":{"present":false,"note":"No Syntology-extracted rows are published in this build."},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}