{"url":"/sota/face-recognition-on-mfr","task":{"name":"Face Recognition","url":"/task/face-recognition","note":null},"dataset":{"name":"MFR","url":"/dataset/mfr"},"category":"Computer Vision","categories":["Computer Vision","Methodology"],"category_note":null,"description":"**Facial Recognition** is the task of making a positive identification of a face in a photo or video image against a pre-existing database of faces. It begins with detection - distinguishing human faces from other objects in the image - and then works on identification of those detected faces.\r\n\r\nThe state of the art tables for this task are contained mainly in the consistent parts of the task : the face verification and face identification tasks.\r\n\r\n<span style=\"color:grey; opacity: 0.6\">( Image credit: [Face Verification](https://shuftipro.com/face-verification) )</span>","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":["MFR-ALL","MFR-MASK","African","Caucasian","South Asian","East Asian"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"MFR-ALL":null,"MFR-MASK":null,"African":null,"Caucasian":null,"South Asian":null,"East Asian":null}},"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":"Partial FC","metrics":{"African":"98.07","Caucasian":"98.81","East Asian":"89.97","MFR-ALL":"97.85","MFR-MASK":"90.88","South Asian":"98.66"},"uses_additional_data":false,"paper_date":"2022-03-28","paper":"/paper/killing-two-birds-with-one-stone-efficient","paper_url":"https://arxiv.org/abs/2203.15565v1","paper_title":"Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC","code":"https://github.com/deepinsight/insightface","n_code_links":6,"syntology":{"n_ran":4,"n_unverified":8,"n_samples":12,"n_pointer_only_licence":4}}],"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":1,"rows_with_any_sample_ran":1,"distinct_papers_with_graph_line":1,"distinct_papers_with_any_sample_ran":1,"samples_over_distinct_papers":{"n_ran":4,"n_unverified":8,"n_samples":12,"n_pointer_only_licence":4,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":4,"n_unverified":8,"n_samples":12,"n_pointer_only_licence":4,"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"}}}