{"url":"/sota/semi-supervised-object-detection-on-coco-0-5","task":{"name":"Semi-Supervised Object Detection","url":"/task/semi-supervised-object-detection","note":null},"dataset":{"name":"COCO 0.5% labeled data","url":null},"category":"Computer Vision","categories":["Computer Vision"],"category_note":null,"description":"Semi-supervised object detection uses both labeled data and unlabeled data for training. It not only reduces the annotation burden for training high-performance object detectors but also further improves the object detector by using a large number of unlabeled data.","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":["mAP"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"mAP":"higher"}},"counts":{"rows":5,"rows_with_code":4,"rows_with_paper_page":5,"rows_dated":5,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"Unbiased Teacher v2","metrics":{"mAP":"21.26 ± 0.21"},"uses_additional_data":false,"paper_date":"2022-06-19","paper":"/paper/unbiased-teacher-v2-semi-supervised-object-1","paper_url":"https://arxiv.org/abs/2206.09500v1","paper_title":"Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors","code":"https://github.com/facebookresearch/unbiased-teacher-v2","n_code_links":1,"syntology":null},{"rank_in_archive_order":2,"model":"Adaptive Rebalancing","metrics":{"mAP":"19.62±0.37"},"uses_additional_data":false,"paper_date":"2021-07-11","paper":"/paper/semi-supervised-object-detection-with-1","paper_url":"https://arxiv.org/abs/2107.05031v1","paper_title":"Semi-Supervised Object Detection with Adaptive Class-Rebalancing Self-Training","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":3,"model":"VC","metrics":{"mAP":"19.46"},"uses_additional_data":false,"paper_date":"2022-07-07","paper":"/paper/semi-supervised-object-detection-via-virtual-1","paper_url":"https://arxiv.org/abs/2207.03433v2","paper_title":"Semi-supervised Object Detection via Virtual Category Learning","code":"https://github.com/geoffreychen777/vc","n_code_links":1,"syntology":null},{"rank_in_archive_order":4,"model":"MUM","metrics":{"mAP":"18.54"},"uses_additional_data":false,"paper_date":"2021-11-22","paper":"/paper/mum-mix-image-tiles-and-unmix-feature-tiles","paper_url":"https://arxiv.org/abs/2111.10958v2","paper_title":"MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection","code":"https://github.com/jongmokkim/mix-unmix","n_code_links":1,"syntology":null},{"rank_in_archive_order":5,"model":"Unbiased Teacher","metrics":{"mAP":"16.94± 0.23"},"uses_additional_data":false,"paper_date":"2021-02-18","paper":"/paper/unbiased-teacher-for-semi-supervised-object-1","paper_url":"https://arxiv.org/abs/2102.09480v1","paper_title":"Unbiased Teacher for Semi-Supervised Object Detection","code":"https://github.com/facebookresearch/unbiased-teacher","n_code_links":4,"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"}}}