{"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/extract-cnn-feature","entry":"extract_cnn_feature","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":14,"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":8,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":15,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":8},"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":"2411.11471","paper":"/paper/generalizable-person-re-identification-via-2","title":"Generalizable Person Re-identification via Balancing Alignment and Uniformity","date":"2024-11-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yoonkicho/BAU","path":"bau/evaluators.py","file_url":"https://github.com/yoonkicho/BAU/blob/HEAD/bau/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"2405.02832","paper":"/paper/fast-one-stage-unsupervised-domain-adaptive","title":"Fast One-Stage Unsupervised Domain Adaptive Person Search","date":"2024-05-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"whbdmu/FOUS","path":"ReLL/evaluators.py","file_url":"https://github.com/whbdmu/FOUS/blob/HEAD/ReLL/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"2402.19026","paper":"/paper/progressive-contrastive-learning-with-multi","title":"Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification","date":"2024-02-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shijiangming1/pclhd","path":"clustercontrast/evaluators.py","file_url":"https://github.com/shijiangming1/pclhd/blob/HEAD/clustercontrast/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5d2252473890de81","mcp_get_code":{"code_sha256":"5d2252473890de81"}},{"arxiv_id":"2311.10605","paper":"/paper/ca-jaccard-camera-aware-jaccard-distance-for","title":"CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification","date":"2023-11-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"chen960/ca-jaccard","path":"caj/evaluators.py","file_url":"https://github.com/chen960/ca-jaccard/blob/HEAD/caj/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"2105.14432","paper":"/paper/transformer-based-deep-image-matching-for","title":"TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification","date":"2021-05-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ShengcaiLiao/QAConv","path":"reid/evaluators.py","file_url":"https://github.com/ShengcaiLiao/QAConv/blob/HEAD/reid/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"124a181591c811ba","mcp_get_code":{"code_sha256":"124a181591c811ba"}},{"arxiv_id":"2103.11658","paper":"/paper/intra-inter-camera-similarity-for","title":"Intra-Inter Camera Similarity for Unsupervised Person Re-Identification","date":"2021-03-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"SY-Xuan/IICS","path":"reid/cluster_utils/cluster.py","file_url":"https://github.com/SY-Xuan/IICS/blob/HEAD/reid/cluster_utils/cluster.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a76ce960a58c48d8","mcp_get_code":{"code_sha256":"a76ce960a58c48d8"}},{"arxiv_id":"2103.11568","paper":"/paper/cluster-contrast-for-unsupervised-person-re","title":"Cluster Contrast for Unsupervised Person Re-Identification","date":"2021-03-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alibaba/cluster-contrast","path":"clustercontrast/evaluators.py","file_url":"https://github.com/alibaba/cluster-contrast/blob/HEAD/clustercontrast/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"2006.12774","paper":"/paper/surpassing-real-world-source-training-data","title":"Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification","date":"2020-06-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VideoObjectSearch/RandPerson","path":"trainCode/Source/reid/evaluators.py","file_url":"https://github.com/VideoObjectSearch/RandPerson/blob/HEAD/trainCode/Source/reid/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"69ea352f5395ae77","mcp_get_code":{"code_sha256":"69ea352f5395ae77"}},{"arxiv_id":"2006.03926","paper":"/paper/self-supervising-fine-grained-region","title":"Self-supervising Fine-grained Region Similarities for Large-scale Image Localization","date":"2020-06-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yxgeee/SFRS","path":"ibl/evaluators.py","file_url":"https://github.com/yxgeee/SFRS/blob/HEAD/ibl/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3be405dcdbc9cbf3","mcp_get_code":{"code_sha256":"3be405dcdbc9cbf3"}},{"arxiv_id":"2003.10071","paper":"/paper/aslfeat-learning-local-features-of-accurate","title":"ASLFeat: Learning Local Features of Accurate Shape and Localization","date":"2020-03-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"YanLiqi/HAF","path":"haf/evaluators.py","file_url":"https://github.com/YanLiqi/HAF/blob/HEAD/haf/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3be405dcdbc9cbf3","mcp_get_code":{"code_sha256":"3be405dcdbc9cbf3"}},{"arxiv_id":"1904.01990","paper":"/paper/invariance-matters-exemplar-memory-for-domain","title":"Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification","date":"2019-04-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhunzhong07/ECN","path":"reid/evaluators.py","file_url":"https://github.com/zhunzhong07/ECN/blob/HEAD/reid/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"f0f55d269b048d70","mcp_get_code":{"code_sha256":"f0f55d269b048d70"}},{"arxiv_id":"1807.09441","paper":"/paper/two-at-once-enhancing-learning-and","title":"Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net","date":"2018-07-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jihaoxuanye/MetaPRD","path":"mprd/evaluators.py","file_url":"https://github.com/jihaoxuanye/MetaPRD/blob/HEAD/mprd/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"aaai_19970","paper":null,"title":"arXiv:aaai_19970","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"LunarShen/SECRET","path":"secret/metrics/evaluators.py","file_url":"https://github.com/LunarShen/SECRET/blob/HEAD/secret/metrics/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}},{"arxiv_id":"aaai_19970","paper":null,"title":"arXiv:aaai_19970","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"LunarShen/SECRET","path":"secret/metrics/Partevaluators.py","file_url":"https://github.com/LunarShen/SECRET/blob/HEAD/secret/metrics/Partevaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"98a65e22d0766c72","mcp_get_code":{"code_sha256":"98a65e22d0766c72"}},{"arxiv_id":"Chen_CA-Jaccard_Camera-aware_Jaccard_Distance_for_Person_Re-identification_CVPR_2024_paper","paper":null,"title":"arXiv:Chen_CA-Jaccard_Camera-aware_Jaccard_Distance_for_Person_Re-identification_CVPR_2024_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"chen960/CA-Jaccard","path":"caj/evaluators.py","file_url":"https://github.com/chen960/CA-Jaccard/blob/HEAD/caj/evaluators.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbb5efeed7ebfd09","mcp_get_code":{"code_sha256":"fbb5efeed7ebfd09"}}]}