{"url":"/sota/interactive-segmentation-on-berkeley","task":{"name":"Interactive Segmentation","url":"/task/interactive-segmentation","note":null},"dataset":{"name":"Berkeley","url":null},"category":"Computer Vision","categories":["Computer Vision"],"category_note":null,"description":null,"description_from":null,"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":["NoC@90","NoC@95"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"NoC@90":null,"NoC@95":null}},"counts":{"rows":14,"rows_with_code":10,"rows_with_paper_page":14,"rows_dated":14,"rows_using_additional_data":1},"rows":[{"rank_in_archive_order":1,"model":"ICL CFR-1 (ViT-H, C+L)","metrics":{"NoC@90":"1.46","NoC@95":"2.90"},"uses_additional_data":false,"paper_date":"2023-03-09","paper":"/paper/cfr-icl-cascade-forward-refinement-with","paper_url":"https://arxiv.org/abs/2303.05620v2","paper_title":"CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image Segmentation","code":"https://github.com/TitorX/CFR-ICL-Interactive-Segmentation","n_code_links":1,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":1}},{"rank_in_archive_order":2,"model":"FocalClick-B3-S2","metrics":{"NoC@90":"1.48"},"uses_additional_data":true,"paper_date":"2022-04-06","paper":"/paper/focalclick-towards-practical-interactive","paper_url":"https://arxiv.org/abs/2204.02574v2","paper_title":"FocalClick: Towards Practical Interactive Image Segmentation","code":"https://github.com/XavierCHEN34/ClickSEG","n_code_links":1,"syntology":{"n_ran":12,"n_unverified":9,"n_samples":21,"n_pointer_only_licence":1}},{"rank_in_archive_order":3,"model":"ViT-B+MST+CL","metrics":{"NoC@90":"1.50"},"uses_additional_data":false,"paper_date":"2024-01-09","paper":"/paper/mst-adaptive-multi-scale-tokens-guided","paper_url":"https://arxiv.org/abs/2401.04403v2","paper_title":"MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation","code":"https://github.com/hahamyt/mst","n_code_links":1,"syntology":null},{"rank_in_archive_order":4,"model":"SimpleClick (ViT-H, C+L)","metrics":{"NoC@90":"1.75"},"uses_additional_data":false,"paper_date":"2022-10-20","paper":"/paper/simpleclick-interactive-image-segmentation","paper_url":"https://arxiv.org/abs/2210.11006v3","paper_title":"SimpleClick: Interactive Image Segmentation with Simple Vision Transformers","code":"https://github.com/uncbiag/simpleclick","n_code_links":2,"syntology":{"n_ran":2,"n_unverified":1,"n_samples":3,"n_pointer_only_licence":1}},{"rank_in_archive_order":5,"model":"SimpleClick (ViT-H, SBD)","metrics":{"NoC@90":"2.09"},"uses_additional_data":false,"paper_date":"2022-10-20","paper":"/paper/simpleclick-interactive-image-segmentation","paper_url":"https://arxiv.org/abs/2210.11006v3","paper_title":"SimpleClick: Interactive Image Segmentation with Simple Vision Transformers","code":"https://github.com/uncbiag/simpleclick","n_code_links":2,"syntology":{"n_ran":2,"n_unverified":1,"n_samples":3,"n_pointer_only_licence":1}},{"rank_in_archive_order":6,"model":"IA-FP-Net(HRNet, C+L)","metrics":{"NoC@90":"2.12"},"uses_additional_data":false,"paper_date":"2022-03-10","paper":"/paper/intention-aware-feature-propagation-network","paper_url":"https://arxiv.org/abs/2203.05145v3","paper_title":"Cascaded Sparse Feature Propagation Network for Interactive Segmentation","code":"https://github.com/kleinzcy/csfpn","n_code_links":1,"syntology":null},{"rank_in_archive_order":7,"model":"RITM (HRNet18, C+L)","metrics":{"NoC@90":"2.26"},"uses_additional_data":false,"paper_date":"2021-02-12","paper":"/paper/reviving-iterative-training-with-mask","paper_url":"https://arxiv.org/abs/2102.06583v1","paper_title":"Reviving Iterative Training with Mask Guidance for Interactive Segmentation","code":"https://github.com/PaddlePaddle/PaddleSeg","n_code_links":5,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":8,"model":"EdgeFlow","metrics":{"NoC@90":"2.4"},"uses_additional_data":false,"paper_date":"2021-09-20","paper":"/paper/edgeflow-achieving-practical-interactive","paper_url":"https://arxiv.org/abs/2109.09406v2","paper_title":"EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow","code":"https://github.com/PaddlePaddle/PaddleSeg","n_code_links":3,"syntology":{"n_ran":2,"n_unverified":3,"n_samples":5,"n_pointer_only_licence":0}},{"rank_in_archive_order":9,"model":"UCP-Net","metrics":{"NoC@90":"2.70"},"uses_additional_data":false,"paper_date":"2021-09-15","paper":"/paper/ucp-net-unstructured-contour-points-for","paper_url":"https://arxiv.org/abs/2109.07592v1","paper_title":"UCP-Net: Unstructured Contour Points for Instance Segmentation","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":10,"model":"RITM (HRNet18, SBD)","metrics":{"NoC@90":"3.22"},"uses_additional_data":false,"paper_date":"2021-02-12","paper":"/paper/reviving-iterative-training-with-mask","paper_url":"https://arxiv.org/abs/2102.06583v1","paper_title":"Reviving Iterative Training with Mask Guidance for Interactive Segmentation","code":"https://github.com/PaddlePaddle/PaddleSeg","n_code_links":5,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":11,"model":"f-BRS-B (ResNet-50)","metrics":{"NoC@90":"4.34"},"uses_additional_data":false,"paper_date":"2020-01-28","paper":"/paper/f-brs-rethinking-backpropagating-refinement","paper_url":"https://arxiv.org/abs/2001.10331v3","paper_title":"f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation","code":"https://github.com/PaddlePaddle/PaddleSeg","n_code_links":2,"syntology":null},{"rank_in_archive_order":12,"model":"IA+SA","metrics":{"NoC@90":"4.94"},"uses_additional_data":false,"paper_date":"2019-11-28","paper":"/paper/continuous-adaptation-for-interactive-object","paper_url":"https://arxiv.org/abs/1911.12709v4","paper_title":"Continuous Adaptation for Interactive Object Segmentation by Learning from Corrections","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":13,"model":"BRS","metrics":{"NoC@90":"5.08"},"uses_additional_data":false,"paper_date":"2019-06-01","paper":"/paper/interactive-image-segmentation-via","paper_url":"http://openaccess.thecvf.com/content_CVPR_2019/html/Jang_Interactive_Image_Segmentation_via_Backpropagating_Refinement_Scheme_CVPR_2019_paper.html","paper_title":"Interactive Image Segmentation via Backpropagating Refinement Scheme","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":14,"model":"CM guidance","metrics":{"NoC@90":"5.60"},"uses_additional_data":false,"paper_date":"2019-06-01","paper":"/paper/content-aware-multi-level-guidance-for","paper_url":"http://openaccess.thecvf.com/content_CVPR_2019/html/Majumder_Content-Aware_Multi-Level_Guidance_for_Interactive_Instance_Segmentation_CVPR_2019_paper.html","paper_title":"Content-Aware Multi-Level Guidance for Interactive Instance Segmentation","code":null,"n_code_links":0,"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":7,"rows_with_any_sample_ran":7,"distinct_papers_with_graph_line":5,"distinct_papers_with_any_sample_ran":5,"samples_over_distinct_papers":{"n_ran":18,"n_unverified":13,"n_samples":31,"n_pointer_only_licence":3,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":21,"n_unverified":14,"n_samples":35,"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"}}}