{"url":"/task/generalizable-person-re-identification","name":"Generalizable Person Re-identification","slug":"generalizable-person-re-identification","description_markdown":"Generalizable person re-identification refers to methods trained on a source dataset but directly evaluated on a target dataset without domain adaptation or transfer learning.","categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":44,"papers_with_code":25,"benchmarks":5,"benchmark_tables_in_archive":5,"benchmark_tables_shown":5,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":11,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/generalizable-person-re-identification-on-21","slug":"generalizable-person-re-identification-on-21","dataset":"Market-1501","dataset_url":"/dataset/market-1501","rows_in_archive":5,"metrics":["ClonedPerson->mAP","ClonedPerson->Rank-1","RandPerson->mAP","RandPerson->Rank-1","MSMT17->mAP","MSMT17->Rank-1","MSMT17-All->mAP","MSMT17-All->Rank-1","DukeMTMC-reID->mAP","DukeMTMC-reID->Rank1"],"first_row_in_archive_order":{"model":"TransMatcher","paper_title":"TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification","paper_url":"/paper/transformer-based-deep-image-matching-for","paper_date":"2021-05-30","arxiv_id":"2105.14432","code_links":[{"title":"shengcailiao/QAConv","url":"https://github.com/shengcailiao/QAConv"},{"title":"ShengcaiLiao/TransMatcher","url":"https://github.com/ShengcaiLiao/TransMatcher"}],"syntology":{"n":21,"n_ran":10,"n_unverified":11,"n_pointer_only":1}}},{"leaderboard":"/sota/generalizable-person-re-identification-on-22","slug":"generalizable-person-re-identification-on-22","dataset":"CUHK03-NP (detected)","dataset_url":"/dataset/cuhk03","rows_in_archive":5,"metrics":["ClonedPerson->mAP","ClonedPerson->Rank-1","RandPerson->mAP","RandPerson->Rank-1","MSMT17->mAP","MSMT17->Rank-1","MSMT17-All->mAP","MSMT17-All->Rank-1","Market-1501->mAP","Market-1501->Rank-1"],"first_row_in_archive_order":{"model":"TransMatcher","paper_title":"TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification","paper_url":"/paper/transformer-based-deep-image-matching-for","paper_date":"2021-05-30","arxiv_id":"2105.14432","code_links":[{"title":"shengcailiao/QAConv","url":"https://github.com/shengcailiao/QAConv"},{"title":"ShengcaiLiao/TransMatcher","url":"https://github.com/ShengcaiLiao/TransMatcher"}],"syntology":{"n":21,"n_ran":10,"n_unverified":11,"n_pointer_only":1}}},{"leaderboard":"/sota/generalizable-person-re-identification-on-20","slug":"generalizable-person-re-identification-on-20","dataset":"MSMT17","dataset_url":"/dataset/msmt17","rows_in_archive":4,"metrics":["ClonedPerson->mAP","ClonedPerson->Rank-1","RandPerson->mAP","RandPerson->Rank-1","Market-1501->mAP","Market-1501->Rank1"],"first_row_in_archive_order":{"model":"TransMatcher","paper_title":"TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification","paper_url":"/paper/transformer-based-deep-image-matching-for","paper_date":"2021-05-30","arxiv_id":"2105.14432","code_links":[{"title":"shengcailiao/QAConv","url":"https://github.com/shengcailiao/QAConv"},{"title":"ShengcaiLiao/TransMatcher","url":"https://github.com/ShengcaiLiao/TransMatcher"}],"syntology":{"n":21,"n_ran":10,"n_unverified":11,"n_pointer_only":1}}},{"leaderboard":"/sota/generalizable-person-re-identification-on-23","slug":"generalizable-person-re-identification-on-23","dataset":"DukeMTMC-reID","dataset_url":"/dataset/dukemtmc-reid","rows_in_archive":4,"metrics":["Market-1501->Rank1","Market-1501->mAP","MSMT17->Rank1","MSMT17->mAP","MSMT17-All->Rank-1","MSMT17-All->mAP","RandPerson->Rank1","RandPerson->mAP"],"first_row_in_archive_order":{"model":"DCAC","paper_title":"Unleashing the Potential of Pre-Trained Diffusion Models for Generalizable Person Re-Identification","paper_url":"/paper/unleashing-the-potential-of-pre-trained","paper_date":"2025-02-10","arxiv_id":"2502.06619","code_links":[{"title":"RikoLi/DCAC","url":"https://github.com/RikoLi/DCAC"}],"syntology":null}},{"leaderboard":"/sota/generalizable-person-re-identification-on-19","slug":"generalizable-person-re-identification-on-19","dataset":"ClonedPerson","dataset_url":"/dataset/clonedperson","rows_in_archive":2,"metrics":["RandPerson->mAP","RandPerson->Rank-1","MSMT17->mAP","MSMT17->Rank-1","Market-1501->mAP","Market-1501->Rank-1"],"first_row_in_archive_order":{"model":"TransMatcher","paper_title":"Is Synthetic Dataset Reliable for Benchmarking Generalizable Person Re-Identification?","paper_url":"/paper/is-synthetic-dataset-reliable-for","paper_date":"2022-09-12","arxiv_id":"2209.05047","code_links":[{"title":"shengcailiao/QAConv","url":"https://github.com/shengcailiao/QAConv"}],"syntology":null}}],"datasets":[{"url":"/dataset/market-1501","name":"Market-1501","full_name":"","num_papers_in_archive":873},{"url":"/dataset/cuhk03","name":"CUHK03","full_name":"Chinese University of Hong Kong Re-identification","num_papers_in_archive":419},{"url":"/dataset/dukemtmc-reid","name":"DukeMTMC-reID","full_name":"","num_papers_in_archive":344},{"url":"/dataset/msmt17","name":"MSMT17","full_name":"Multi Scene Multi Time dataset for person re-id","num_papers_in_archive":275},{"url":"/dataset/market-1501-c","name":"Market-1501-C","full_name":"Market-1501-C","num_papers_in_archive":22},{"url":"/dataset/cuhk03-c","name":"CUHK03-C","full_name":"CUHK03-C","num_papers_in_archive":9},{"url":"/dataset/clonedperson","name":"ClonedPerson","full_name":"","num_papers_in_archive":6},{"url":"/dataset/msmt17-c","name":"MSMT17-C","full_name":"MSMT17-C","num_papers_in_archive":5},{"url":"/dataset/regdb-c","name":"RegDB-C","full_name":"RegDB-C","num_papers_in_archive":4},{"url":"/dataset/sysu-mm01-c","name":"SYSU-MM01-C","full_name":"SYSU-MM01-C","num_papers_in_archive":4},{"url":"/dataset/entire-id","name":"ENTIRe-ID","full_name":"ENTIRe-ID","num_papers_in_archive":1}],"subtasks":[],"parent_tasks":[{"url":"/task/person-re-identification","name":"Person Re-Identification"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":25,"of":25,"tagged_in_all":44,"items":[{"url":"/paper/semi-supervised-domain-generalizable-person","title":"Semi-Supervised Domain Generalizable Person Re-Identification","date":"2021-08-11","arxiv_id":"2108.05045","repositories_listed":3,"syntology":{"n":7,"n_ran":6,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/generalizable-person-re-identification-via-2","title":"Generalizable Person Re-identification via Balancing Alignment and Uniformity","date":"2024-11-18","arxiv_id":"2411.11471","repositories_listed":2,"syntology":{"n":15,"n_ran":4,"n_unverified":11,"n_pointer_only":0}},{"url":"/paper/identity-seeking-self-supervised","title":"Identity-Seeking Self-Supervised Representation Learning for Generalizable Person Re-identification","date":"2023-08-17","arxiv_id":"2308.08887","repositories_listed":2,"syntology":null},{"url":"/paper/cloning-outfits-from-real-world-images-to-3d","title":"Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification","date":"2022-04-06","arxiv_id":"2204.02611","repositories_listed":2,"syntology":null},{"url":"/paper/transformer-based-deep-image-matching-for","title":"TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification","date":"2021-05-30","arxiv_id":"2105.14432","repositories_listed":2,"syntology":{"n":21,"n_ran":10,"n_unverified":11,"n_pointer_only":1}},{"url":"/paper/following-the-clues-experiments-on-person-re","title":"Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence","date":"2025-07-02","arxiv_id":"2507.01504","repositories_listed":1,"syntology":null},{"url":"/paper/unleashing-the-potential-of-pre-trained","title":"Unleashing the Potential of Pre-Trained Diffusion Models for Generalizable Person Re-Identification","date":"2025-02-10","arxiv_id":"2502.06619","repositories_listed":1,"syntology":null},{"url":"/paper/cilp-fgdi-exploiting-vision-language-model","title":"CILP-FGDI: Exploiting Vision-Language Model for Generalizable Person Re-Identification","date":"2025-01-27","arxiv_id":"2501.16065","repositories_listed":1,"syntology":null},{"url":"/paper/part-aware-transformer-for-generalizable","title":"Part-Aware Transformer for Generalizable Person Re-identification","date":"2023-08-07","arxiv_id":"2308.03322","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_unverified":1,"n_pointer_only":11}},{"url":"/paper/learning-robust-visual-semantic-embedding-for","title":"Learning Robust Visual-Semantic Embedding for Generalizable Person Re-identification","date":"2023-04-19","arxiv_id":"2304.09498","repositories_listed":1,"syntology":null},{"url":"/paper/deep-multimodal-fusion-for-generalizable","title":"Deep Multimodal Fusion for Generalizable Person Re-identification","date":"2022-11-02","arxiv_id":"2211.00933","repositories_listed":1,"syntology":null},{"url":"/paper/style-variable-and-irrelevant-learning-for","title":"Style Variable and Irrelevant Learning for Generalizable Person Re-identification","date":"2022-09-12","arxiv_id":"2209.05235","repositories_listed":1,"syntology":null},{"url":"/paper/is-synthetic-dataset-reliable-for","title":"Is Synthetic Dataset Reliable for Benchmarking Generalizable Person Re-Identification?","date":"2022-09-12","arxiv_id":"2209.05047","repositories_listed":1,"syntology":null},{"url":"/paper/style-interleaved-learning-for-generalizable","title":"Style Interleaved Learning for Generalizable Person Re-identification","date":"2022-07-07","arxiv_id":"2207.03132","repositories_listed":1,"syntology":null},{"url":"/paper/meta-distribution-alignment-for-generalizable","title":"Meta Distribution Alignment for Generalizable Person Re-Identification","date":"2022-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/meta-mimicking-embedding-via-others","title":"Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification","date":"2021-12-16","arxiv_id":"2112.08684","repositories_listed":1,"syntology":null},{"url":"/paper/calibrated-feature-decomposition-for","title":"Calibrated Feature Decomposition for Generalizable Person Re-Identification","date":"2021-11-27","arxiv_id":"2111.13945","repositories_listed":1,"syntology":null},{"url":"/paper/benchmarks-for-corruption-invariant-person-re","title":"Benchmarks for Corruption Invariant Person Re-identification","date":"2021-11-01","arxiv_id":"2111.00880","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/graph-sampling-based-deep-metric-learning-for","title":"Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification","date":"2021-04-04","arxiv_id":"2104.01546","repositories_listed":1,"syntology":null},{"url":"/paper/meta-batch-instance-normalization-for","title":"Meta Batch-Instance Normalization for Generalizable Person Re-Identification","date":"2020-11-30","arxiv_id":"2011.14670","repositories_listed":1,"syntology":null},{"url":"/paper/domainmix-learning-generalizable-person-re","title":"DomainMix: Learning Generalizable Person Re-Identification Without Human Annotations","date":"2020-11-24","arxiv_id":"2011.11953","repositories_listed":1,"syntology":null},{"url":"/paper/dual-distribution-alignment-network-for","title":"Dual Distribution Alignment Network for Generalizable Person Re-Identification","date":"2020-07-27","arxiv_id":"2007.13249","repositories_listed":1,"syntology":null},{"url":"/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","arxiv_id":"2006.12774","repositories_listed":1,"syntology":{"n":9,"n_ran":0,"n_unverified":9,"n_pointer_only":0}},{"url":"/paper/style-normalization-and-restitution-for","title":"Style Normalization and Restitution for Generalizable Person Re-identification","date":"2020-05-22","arxiv_id":"2005.11037","repositories_listed":1,"syntology":null},{"url":"/paper/interpretable-and-generalizable-deep-image","title":"Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting","date":"2019-04-23","arxiv_id":"1904.10424","repositories_listed":1,"syntology":null}],"syntology_records":6,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","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)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}