{"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":"/paper/unsupervised-domain-adaptive-re","title":"Unsupervised Domain Adaptive Re-Identification: Theory and Practice","arxiv_id":"1807.11334","date":"2018-07-30","proceeding":null,"authors":["Liangchen Song","Cheng Wang","Lefei Zhang","Bo Du","Qian Zhang","Chang Huang","Xinggang Wang"],"abstract":"We study the problem of unsupervised domain adaptive re-identification\n(re-ID) which is an active topic in computer vision but lacks a theoretical\nfoundation. We first extend existing unsupervised domain adaptive\nclassification theories to re-ID tasks. Concretely, we introduce some\nassumptions on the extracted feature space and then derive several loss\nfunctions guided by these assumptions. To optimize them, a novel self-training\nscheme for unsupervised domain adaptive re-ID tasks is proposed. It iteratively\nmakes guesses for unlabeled target data based on an encoder and trains the\nencoder based on the guessed labels. Extensive experiments on unsupervised\ndomain adaptive person re-ID and vehicle re-ID tasks with comparisons to the\nstate-of-the-arts confirm the effectiveness of the proposed theories and\nself-training framework. Our code is available at\n\\url{https://github.com/LcDog/DomainAdaptiveReID}.","url_abs":"http://arxiv.org/abs/1807.11334v1","url_pdf":"http://arxiv.org/pdf/1807.11334v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"unsupervised-domain-adaptive-re","repo_url":"https://github.com/LcDog/DomainAdaptiveReID","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"unsupervised-domain-adaptive-re","repo_url":"https://github.com/FlyingRoastDuck/ACT_AAAI20","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"unsupervised-domain-adaptive-re","repo_url":"https://github.com/TencentYoutuResearch/PersonReID-ACT","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"unsupervised-domain-adaptation","task_name":"Unsupervised Domain Adaptation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/unsupervised-domain-adaptation-on-duke-to","task":"Unsupervised Domain Adaptation","dataset":"Duke to Market","model":"UDAP","rank_in_archive_order":16,"of":26,"metrics":{"mAP":"53.7","rank-1":"75.8","rank-10":"93.2","rank-5":"89.5"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-market-to-6","task":"Unsupervised Domain Adaptation","dataset":"Market to CUHK03","model":"UDAR","rank_in_archive_order":6,"of":8,"metrics":{"R1":"20.3","R10":"-","R5":"-","mAP":"20.9"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-market-to","task":"Unsupervised Domain Adaptation","dataset":"Market to Duke","model":"UDAP","rank_in_archive_order":16,"of":25,"metrics":{"mAP":"49.0","rank-1":"68.4","rank-10":"83.5","rank-5":"80.1"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-vehicleid-3","task":"Unsupervised Domain Adaptation","dataset":"VehicleID to VERI-Wild Large","model":"UDAR","rank_in_archive_order":5,"of":9,"metrics":{"R-1":"53.7","R-10":"-","R-5":"73.9","mAP":"20.8"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-vehicleid-2","task":"Unsupervised Domain Adaptation","dataset":"VehicleID to VERI-Wild Medium","model":"UDAR","rank_in_archive_order":4,"of":9,"metrics":{"R-1":"62.5","R-10":"-","R-5":"81.8","mAP":"26.2"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-vehicleid-1","task":"Unsupervised Domain Adaptation","dataset":"VehicleID to VERI-Wild Small","model":"UDAR","rank_in_archive_order":4,"of":9,"metrics":{"R-1":"68.4","R-10":"-","R-5":"85.3","mAP":"30.0"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-vehicleid","task":"Unsupervised Domain Adaptation","dataset":"VehicleID to VeRi-776","model":"UDAR","rank_in_archive_order":9,"of":14,"metrics":{"Rank-1":"76.9","Rank-10":"89.0","Rank-5":"85.8","mAP":"35.8"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-veri-776-to-2","task":"Unsupervised Domain Adaptation","dataset":"Veri-776 to VehicleID Large","model":"UDAR","rank_in_archive_order":4,"of":13,"metrics":{"R-1":"45.20","R-10":"69.14","R-5":"62.60","mAP":"52.90"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-veri-776-to-1","task":"Unsupervised Domain Adaptation","dataset":"Veri-776 to VehicleID Medium","model":"UDAR","rank_in_archive_order":4,"of":13,"metrics":{"R-1":"48.10","R-10":"70.20","R-5":"64.10","mAP":"55.30"},"uses_additional_data":false},{"leaderboard":"/sota/unsupervised-domain-adaptation-on-veri-776-to","task":"Unsupervised Domain Adaptation","dataset":"Veri-776 to VehicleID Small","model":"UDAR","rank_in_archive_order":4,"of":8,"metrics":{" mAP":"59.60","R-1":"54.00","R-10":"72.01","R-5":"66.10"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1807.11334","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.11334"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/FlyingRoastDuck/ACT_AAAI20","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/TencentYoutuResearch/PersonReID-ACT","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/LcDog/DomainAdaptiveReID","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":5},"by_repo_kind":{"official":{"samples":5,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"8435b1758ce9651d","entry":"evaluate_all","repo":"LcDog/DomainAdaptiveReID","repo_kind":"official","path":"reid/evaluators.py","file_url":"https://github.com/LcDog/DomainAdaptiveReID/blob/HEAD/reid/evaluators.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8435b1758ce9651d"}},{"code_sha256_prefix":"334bb1b1add56179","entry":"extract_features","repo":"LcDog/DomainAdaptiveReID","repo_kind":"official","path":"reid/evaluators.py","file_url":"https://github.com/LcDog/DomainAdaptiveReID/blob/HEAD/reid/evaluators.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"334bb1b1add56179"}},{"code_sha256_prefix":"48cf1aad1e6a206d","entry":"oim","repo":"LcDog/DomainAdaptiveReID","repo_kind":"official","path":"reid/loss/oim.py","file_url":"https://github.com/LcDog/DomainAdaptiveReID/blob/HEAD/reid/loss/oim.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"48cf1aad1e6a206d"}},{"code_sha256_prefix":"ce0b73cd063c699a","entry":"pairwise_distance","repo":"LcDog/DomainAdaptiveReID","repo_kind":"official","path":"reid/evaluators.py","file_url":"https://github.com/LcDog/DomainAdaptiveReID/blob/HEAD/reid/evaluators.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"ce0b73cd063c699a"}},{"code_sha256_prefix":"e6a2d08152319c66","entry":"re_ranking","repo":"LcDog/DomainAdaptiveReID","repo_kind":"official","path":"reid/rerank.py","file_url":"https://github.com/LcDog/DomainAdaptiveReID/blob/HEAD/reid/rerank.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e6a2d08152319c66"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}