{"url":"/sota/weakly-supervised-object-detection-on-4","task":{"name":"Weakly Supervised Object Detection","url":"/task/weakly-supervised-object-detection","note":null},"dataset":{"name":"Charades","url":"/dataset/charades"},"category":"Computer Vision","categories":["Computer Vision"],"category_note":null,"description":"Weakly Supervised Object Detection (WSOD) is the task of training object detectors with only image tag supervisions.\r\n\r\n<span style=\"color:grey; opacity: 0.6\">( Image credit: [Soft Proposal Networks for Weakly Supervised Object Localization](https://arxiv.org/pdf/1709.01829v1.pdf) )</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":["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":6,"rows_with_code":4,"rows_with_paper_page":6,"rows_dated":6,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"Spatial Prior","metrics":{"MAP":"10.03"},"uses_additional_data":false,"paper_date":"2019-04-02","paper":"/paper/activity-driven-weakly-supervised-object","paper_url":"http://arxiv.org/abs/1904.01665v1","paper_title":"Activity Driven Weakly Supervised Object Detection","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":2,"model":"PCL","metrics":{"MAP":"2.83"},"uses_additional_data":false,"paper_date":"2018-07-09","paper":"/paper/pcl-proposal-cluster-learning-for-weakly","paper_url":"http://arxiv.org/abs/1807.03342v2","paper_title":"PCL: Proposal Cluster Learning for Weakly Supervised Object Detection","code":"https://github.com/ppengtang/pcl.pytorch","n_code_links":4,"syntology":{"n_ran":1,"n_unverified":6,"n_samples":7,"n_pointer_only_licence":0}},{"rank_in_archive_order":3,"model":"TD-LSTM","metrics":{"MAP":"1.98"},"uses_additional_data":false,"paper_date":"2017-08-02","paper":"/paper/temporal-dynamic-graph-lstm-for-action-driven","paper_url":"http://arxiv.org/abs/1708.00666v1","paper_title":"Temporal Dynamic Graph LSTM for Action-driven Video Object Detection","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":4,"model":"ContextLocNet","metrics":{"MAP":"1.12"},"uses_additional_data":false,"paper_date":"2016-09-14","paper":"/paper/contextlocnet-context-aware-deep-network","paper_url":"http://arxiv.org/abs/1609.04331v1","paper_title":"ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization","code":"https://github.com/vadimkantorov/contextlocnet","n_code_links":1,"syntology":null},{"rank_in_archive_order":5,"model":"R*CNN","metrics":{"MAP":"0.99"},"uses_additional_data":false,"paper_date":"2015-05-05","paper":"/paper/contextual-action-recognition-with-rcnn","paper_url":"http://arxiv.org/abs/1505.01197v3","paper_title":"Contextual Action Recognition with R*CNN","code":"https://github.com/gkioxari/RstarCNN","n_code_links":2,"syntology":null},{"rank_in_archive_order":6,"model":"WSDDN","metrics":{"MAP":"0.65"},"uses_additional_data":false,"paper_date":"2015-11-09","paper":"/paper/weakly-supervised-deep-detection-networks","paper_url":"http://arxiv.org/abs/1511.02853v4","paper_title":"Weakly Supervised Deep Detection Networks","code":"https://github.com/hbilen/WSDDN","n_code_links":5,"syntology":{"n_ran":1,"n_unverified":2,"n_samples":3,"n_pointer_only_licence":1}}],"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":2,"rows_with_any_sample_ran":2,"distinct_papers_with_graph_line":2,"distinct_papers_with_any_sample_ran":2,"samples_over_distinct_papers":{"n_ran":2,"n_unverified":8,"n_samples":10,"n_pointer_only_licence":1,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":2,"n_unverified":8,"n_samples":10,"n_pointer_only_licence":1,"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"}}}