{"url":"/sota/unsupervised-person-re-identification-on-4","task":{"name":"Unsupervised Person Re-Identification","url":"/task/unsupervised-person-re-identification","note":null},"dataset":{"name":"Market-1501","url":"/dataset/market-1501"},"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":["MAP","Rank-1","Rank-5","Rank-10"],"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","Rank-1":null,"Rank-5":null,"Rank-10":null}},"counts":{"rows":23,"rows_with_code":22,"rows_with_paper_page":23,"rows_dated":23,"rows_using_additional_data":3},"rows":[{"rank_in_archive_order":1,"model":"TransReID-SSL (ViTi-S)","metrics":{"MAP":"89.6","Rank-1":"95.3"},"uses_additional_data":true,"paper_date":"2021-11-23","paper":"/paper/self-supervised-pre-training-for-transformer","paper_url":"https://arxiv.org/abs/2111.12084v1","paper_title":"Self-Supervised Pre-Training for Transformer-Based Person Re-Identification","code":"https://github.com/DengpanFu/LUPerson","n_code_links":3,"syntology":{"n_ran":3,"n_unverified":5,"n_samples":8,"n_pointer_only_licence":8}},{"rank_in_archive_order":2,"model":"TMGF","metrics":{"MAP":"89.5","Rank-1":"95.5","Rank-10":"98.7","Rank-5":"98.0"},"uses_additional_data":false,"paper_date":"2022-11-22","paper":"/paper/transformer-based-multi-grained-features-for","paper_url":"https://arxiv.org/abs/2211.12280v1","paper_title":"Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification","code":"https://github.com/rikoli/wacv23-workshop-tmgf","n_code_links":1,"syntology":null},{"rank_in_archive_order":3,"model":"PCL-CLIP (O2CAP)","metrics":{"MAP":"88.4","Rank-1":"94.8","Rank-10":"98.7","Rank-5":"98.0"},"uses_additional_data":false,"paper_date":"2023-10-26","paper":"/paper/prototypical-contrastive-learning-based-clip","paper_url":"https://arxiv.org/abs/2310.17218v1","paper_title":"Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification","code":"https://github.com/RikoLi/PCL-CLIP","n_code_links":1,"syntology":null},{"rank_in_archive_order":4,"model":"TransReID-SSL (ViT-S)","metrics":{"MAP":"88.2","Rank-1":"94.2"},"uses_additional_data":true,"paper_date":"2021-11-23","paper":"/paper/self-supervised-pre-training-for-transformer","paper_url":"https://arxiv.org/abs/2111.12084v1","paper_title":"Self-Supervised Pre-Training for Transformer-Based Person Re-Identification","code":"https://github.com/DengpanFu/LUPerson","n_code_links":3,"syntology":{"n_ran":3,"n_unverified":5,"n_samples":8,"n_pointer_only_licence":8}},{"rank_in_archive_order":5,"model":"PCL-CLIP (CAP)","metrics":{"MAP":"87.4","Rank-1":"93.9","Rank-10":"98.5","Rank-5":"97.7"},"uses_additional_data":false,"paper_date":"2023-10-26","paper":"/paper/prototypical-contrastive-learning-based-clip","paper_url":"https://arxiv.org/abs/2310.17218v1","paper_title":"Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification","code":"https://github.com/RikoLi/PCL-CLIP","n_code_links":1,"syntology":null},{"rank_in_archive_order":6,"model":"PCL-CLIP (CC)","metrics":{"MAP":"86.9","Rank-1":"94.2","Rank-10":"98.7","Rank-5":"97.8"},"uses_additional_data":false,"paper_date":"2023-10-26","paper":"/paper/prototypical-contrastive-learning-based-clip","paper_url":"https://arxiv.org/abs/2310.17218v1","paper_title":"Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification","code":"https://github.com/RikoLi/PCL-CLIP","n_code_links":1,"syntology":null},{"rank_in_archive_order":7,"model":"CA-Jaccard","metrics":{"MAP":"86.1","Rank-1":"94.4","Rank-10":"98.7","Rank-5":"97.9"},"uses_additional_data":false,"paper_date":"2023-11-17","paper":"/paper/ca-jaccard-camera-aware-jaccard-distance-for","paper_url":"https://arxiv.org/abs/2311.10605v2","paper_title":"CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification","code":"https://github.com/chen960/ca-jaccard","n_code_links":1,"syntology":{"n_ran":5,"n_unverified":5,"n_samples":10,"n_pointer_only_licence":0}},{"rank_in_archive_order":8,"model":"PPLR","metrics":{"MAP":"84.4","Rank-1":"94.3","Rank-10":"98.6","Rank-5":"97.8"},"uses_additional_data":false,"paper_date":"2022-03-28","paper":"/paper/part-based-pseudo-label-refinement-for","paper_url":"https://arxiv.org/abs/2203.14675v1","paper_title":"Part-based Pseudo Label Refinement for Unsupervised Person Re-identification","code":"https://github.com/yoonkicho/pplr","n_code_links":1,"syntology":{"n_ran":4,"n_unverified":1,"n_samples":5,"n_pointer_only_licence":0}},{"rank_in_archive_order":9,"model":"HHCL(ResNet50 w/o RK)","metrics":{"MAP":"84.2","Rank-1":"93.4","Rank-10":"98.5","Rank-5":"97.7"},"uses_additional_data":false,"paper_date":"2021-09-25","paper":"/paper/hard-sample-guided-hybrid-contrast-learning","paper_url":"https://arxiv.org/abs/2109.12333v2","paper_title":"Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-Identification","code":"https://github.com/bupt-ai-cz/hhcl-reid","n_code_links":1,"syntology":null},{"rank_in_archive_order":10,"model":"Cluster Contrast","metrics":{"MAP":"83","Rank-1":"92.9","Rank-10":"98","Rank-5":"97.2"},"uses_additional_data":false,"paper_date":"2021-03-22","paper":"/paper/cluster-contrast-for-unsupervised-person-re","paper_url":"https://arxiv.org/abs/2103.11568v4","paper_title":"Cluster Contrast for Unsupervised Person Re-Identification","code":"https://github.com/alibaba/cluster-contrast","n_code_links":4,"syntology":{"n_ran":8,"n_unverified":6,"n_samples":14,"n_pointer_only_licence":0}},{"rank_in_archive_order":11,"model":"ICE","metrics":{"MAP":"82.3","Rank-1":"93.8","Rank-10":"98.4","Rank-5":"97.6"},"uses_additional_data":false,"paper_date":"2021-03-30","paper":"/paper/ice-inter-instance-contrastive-encoding-for","paper_url":"https://arxiv.org/abs/2103.16364v2","paper_title":"ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification","code":"https://github.com/chenhao2345/ICE","n_code_links":1,"syntology":{"n_ran":1,"n_unverified":0,"n_samples":1,"n_pointer_only_licence":0}},{"rank_in_archive_order":12,"model":"CACL","metrics":{"MAP":"80.9","Rank-1":"92.7","Rank-10":"98.5","Rank-5":"97.4"},"uses_additional_data":false,"paper_date":"2021-06-15","paper":"/paper/cluster-guided-asymmetric-contrastive","paper_url":"https://arxiv.org/abs/2106.07846v2","paper_title":"Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification","code":"https://github.com/MingkunLishigure/CACL","n_code_links":1,"syntology":null},{"rank_in_archive_order":13,"model":"MGCE-HCL","metrics":{"MAP":"79.6","Rank-1":"92.1"},"uses_additional_data":false,"paper_date":"2022-01-28","paper":"/paper/hybrid-contrastive-learning-with-cluster","paper_url":"https://arxiv.org/abs/2201.11995v2","paper_title":"Hybrid Contrastive Learning with Cluster Ensemble for Unsupervised Person Re-identification","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":14,"model":"Group Sampling","metrics":{"MAP":"79.2","Rank-1":"92.3","Rank-10":"97.8","Rank-5":"96.6"},"uses_additional_data":false,"paper_date":"2021-07-07","paper":"/paper/group-sampling-for-unsupervised-person-re","paper_url":"https://arxiv.org/abs/2107.03024v4","paper_title":"Rethinking Sampling Strategies for Unsupervised Person Re-identification","code":"https://github.com/ucas-vg/groupsampling","n_code_links":2,"syntology":null},{"rank_in_archive_order":15,"model":"CAP","metrics":{"MAP":"79.2","Rank-1":"91.4","Rank-10":"97.7","Rank-5":"96.3"},"uses_additional_data":false,"paper_date":"2020-12-19","paper":"/paper/camera-aware-proxies-for-unsupervised-person","paper_url":"https://arxiv.org/abs/2012.10674v2","paper_title":"Camera-aware Proxies for Unsupervised Person Re-Identification","code":"https://github.com/Terminator8758/CAP-master","n_code_links":1,"syntology":null},{"rank_in_archive_order":16,"model":"IICS","metrics":{"MAP":"72.9","Rank-1":"89.5","Rank-10":"97.0","Rank-5":"95.2"},"uses_additional_data":false,"paper_date":"2021-03-22","paper":"/paper/intra-inter-camera-similarity-for","paper_url":"https://arxiv.org/abs/2103.11658v1","paper_title":"Intra-Inter Camera Similarity for Unsupervised Person Re-Identification","code":"https://github.com/SY-Xuan/IICS","n_code_links":1,"syntology":{"n_ran":5,"n_unverified":3,"n_samples":8,"n_pointer_only_licence":8}},{"rank_in_archive_order":17,"model":"SpCL","metrics":{"MAP":"72.6","Rank-1":"87.7","Rank-10":"96.9","Rank-5":"95.2"},"uses_additional_data":false,"paper_date":"2020-06-04","paper":"/paper/self-paced-contrastive-learning-with-hybrid","paper_url":"https://arxiv.org/abs/2006.02713v2","paper_title":"Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID","code":"https://github.com/open-mmlab/OpenUnReID","n_code_links":3,"syntology":{"n_ran":3,"n_unverified":2,"n_samples":5,"n_pointer_only_licence":0}},{"rank_in_archive_order":18,"model":"Self-Similarity Grouping (one shot)","metrics":{"MAP":"71.5","Rank-1":"87.5","Rank-10":"96.8","Rank-5":"95.2"},"uses_additional_data":false,"paper_date":"2018-11-26","paper":"/paper/one-shot-domain-adaptation-for-person-re","paper_url":"https://arxiv.org/abs/1811.10144v3","paper_title":"Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification","code":"https://github.com/OasisYang/SSG","n_code_links":1,"syntology":null},{"rank_in_archive_order":19,"model":"ECN","metrics":{"MAP":"43","Rank-1":"75.1","Rank-10":"91.6","Rank-5":"87.6"},"uses_additional_data":false,"paper_date":"2019-04-03","paper":"/paper/invariance-matters-exemplar-memory-for-domain","paper_url":"http://arxiv.org/abs/1904.01990v1","paper_title":"Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification","code":"https://github.com/zhunzhong07/ECN","n_code_links":2,"syntology":{"n_ran":0,"n_unverified":8,"n_samples":8,"n_pointer_only_licence":0}},{"rank_in_archive_order":20,"model":"Dispersion based Clustering","metrics":{"MAP":"41.3","Rank-1":"69.2","Rank-10":"87.8","Rank-5":"83"},"uses_additional_data":false,"paper_date":"2019-06-04","paper":"/paper/towards-better-validity-dispersion-based","paper_url":"https://arxiv.org/abs/1906.01308v1","paper_title":"Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification","code":"https://github.com/gddingcs/Dispersion-based-Clustering","n_code_links":1,"syntology":null},{"rank_in_archive_order":21,"model":"SPGAN+LMP","metrics":{"MAP":"26.7","Rank-1":"57.7","Rank-10":"82.4","Rank-5":"75.8"},"uses_additional_data":false,"paper_date":"2017-11-19","paper":"/paper/image-image-domain-adaptation-with-preserved","paper_url":"http://arxiv.org/abs/1711.07027v3","paper_title":"Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification","code":"https://github.com/thuml/Transfer-Learning-Library","n_code_links":2,"syntology":null},{"rank_in_archive_order":22,"model":"PUL","metrics":{"MAP":"20.5","Rank-1":"45.5","Rank-10":"66.7","Rank-5":"60.7"},"uses_additional_data":false,"paper_date":"2017-05-30","paper":"/paper/unsupervised-person-re-identification","paper_url":"http://arxiv.org/abs/1705.10444v2","paper_title":"Unsupervised Person Re-identification: Clustering and Fine-tuning","code":"https://github.com/hehefan/Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning","n_code_links":1,"syntology":null},{"rank_in_archive_order":23,"model":"TransReID-SSL (ViT-S w/o RK)","metrics":{"Rank-1":"95.3"},"uses_additional_data":true,"paper_date":"2021-11-23","paper":"/paper/self-supervised-pre-training-for-transformer","paper_url":"https://arxiv.org/abs/2111.12084v1","paper_title":"Self-Supervised Pre-Training for Transformer-Based Person Re-Identification","code":"https://github.com/DengpanFu/LUPerson","n_code_links":3,"syntology":{"n_ran":3,"n_unverified":5,"n_samples":8,"n_pointer_only_licence":8}}],"since_archive":{"claim":"Results that newer papers report for their own method, placed here by Syntology. A model pointed at the cell in the paper's own table; the number was read from that cell and checked against this leaderboard's metric, dataset, split and scale; an independent check that saw this leaderboard's other rows and every other leaderboard on the same dataset accepted it. Not reviewed by the paper's authors or by the archive's editors, and not ranked against the archive rows.","extraction_file_present":true,"measurement":{"test_papers":883,"papers_with_output":881,"judged_true":108,"judged":110,"wilson95_lower":0.9361,"measured_on":"2026-09-24","frozen_commit":"0e3de0df94"},"measurement_note":"blind adjudication of accepted entries on a held-out split of archive papers, rules frozen before the test","coverage":{"sentence":"Syntology has checked 6,821 of the 9,623 papers on this site that are newer than the archive; results from the others appear after they are checked.","complete":false,"papers_newer_than_archive":9623,"papers_checked":6821,"papers_extracted_not_yet_verified":65,"boards_without_verdict":29,"papers_not_yet_extracted":2737},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-25T09:33:49+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":10,"rows_with_any_sample_ran":9,"distinct_papers_with_graph_line":8,"distinct_papers_with_any_sample_ran":7,"samples_over_distinct_papers":{"n_ran":29,"n_unverified":30,"n_samples":59,"n_pointer_only_licence":16,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":35,"n_unverified":40,"n_samples":75,"n_pointer_only_licence":32,"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"}}}