{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/non-maximum-suppression","entry":"non_maximum_suppression","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":8,"n_papers_ran":0,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":7,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":9,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":7},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2505.23475","paper":"/paper/timepoint-accelerated-time-series-alignment","title":"TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning","date":"2025-05-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bgu-cs-vil/timepoint","path":"TimePoint/models/timepoint.py","file_url":"https://github.com/bgu-cs-vil/timepoint/blob/HEAD/TimePoint/models/timepoint.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a1c12bb3fb090024","mcp_get_code":{"code_sha256":"a1c12bb3fb090024"}},{"arxiv_id":"2207.14288","paper":"/paper/rewriting-geometric-rules-of-a-gan","title":"Rewriting Geometric Rules of a GAN","date":"2022-07-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"peterwang512/ganwarping","path":"evaluation/chamfer_evaluator.py","file_url":"https://github.com/peterwang512/ganwarping/blob/HEAD/evaluation/chamfer_evaluator.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f377d184b49df220","mcp_get_code":{"code_sha256":"f377d184b49df220"}},{"arxiv_id":"2203.02284","paper":"/paper/nuclei-segmentation-and-classification-in","title":"Nuclei instance segmentation and classification in histopathology images with StarDist","date":"2022-03-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mpicbg-csbd/stardist","path":"stardist/nms.py","file_url":"https://github.com/mpicbg-csbd/stardist/blob/HEAD/stardist/nms.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"e2dcd6ed644b4198","mcp_get_code":{"code_sha256":"e2dcd6ed644b4198"}},{"arxiv_id":"2104.11207","paper":"/paper/fully-convolutional-line-parsing","title":"Fully Convolutional Line Parsing","date":"2021-04-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Delay-Xili/F-Clip","path":"FClip/nms.py","file_url":"https://github.com/Delay-Xili/F-Clip/blob/HEAD/FClip/nms.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a58f56d0f6bd4d2a","mcp_get_code":{"code_sha256":"a58f56d0f6bd4d2a"}},{"arxiv_id":"2103.15087","paper":"/paper/learning-a-sketch-tensor-space-for-image","title":"Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes","date":"2021-03-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ewrfcas/MST_inpainting","path":"src/lsm_hawp/detector.py","file_url":"https://github.com/ewrfcas/MST_inpainting/blob/HEAD/src/lsm_hawp/detector.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c972983944d63a38","mcp_get_code":{"code_sha256":"c972983944d63a38"}},{"arxiv_id":"2007.08139","paper":"/paper/interactive-video-object-segmentation-using","title":"Interactive Video Object Segmentation Using Global and Local Transfer Modules","date":"2020-07-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dongkwonjin/Semantic-Line-SLNet","path":"Modelling/code/libs/modules.py","file_url":"https://github.com/dongkwonjin/Semantic-Line-SLNet/blob/HEAD/Modelling/code/libs/modules.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1952b3a21e3326a1","mcp_get_code":{"code_sha256":"1952b3a21e3326a1"}},{"arxiv_id":"1905.03246","paper":"/paper/190503246","title":"End-to-End Wireframe Parsing","date":"2019-05-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhou13/lcnn","path":"lcnn/models/line_vectorizer.py","file_url":"https://github.com/zhou13/lcnn/blob/HEAD/lcnn/models/line_vectorizer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c972983944d63a38","mcp_get_code":{"code_sha256":"c972983944d63a38"}},{"arxiv_id":"1806.03535","paper":"/paper/cell-detection-with-star-convex-polygons","title":"Cell Detection with Star-convex Polygons","date":"2018-06-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hthierno/pytorch-stardist","path":"stardist_tools_/stardist_tools/nms.py","file_url":"https://github.com/hthierno/pytorch-stardist/blob/HEAD/stardist_tools_/stardist_tools/nms.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"e2dcd6ed644b4198","mcp_get_code":{"code_sha256":"e2dcd6ed644b4198"}},{"arxiv_id":"1806.03535","paper":"/paper/cell-detection-with-star-convex-polygons","title":"Cell Detection with Star-convex Polygons","date":"2018-06-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"uhlmanngroup/splinedist","path":"splinedist/nms.py","file_url":"https://github.com/uhlmanngroup/splinedist/blob/HEAD/splinedist/nms.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"141dc23558e58934","mcp_get_code":{"code_sha256":"141dc23558e58934"}}]}