{"id":"https://openalex.org/W4415539733","doi":"https://doi.org/10.1145/3746027.3755580","title":"Decoupled Identity and Attribute Tokenization for Person Re-Identification","display_name":"Decoupled Identity and Attribute Tokenization for Person Re-Identification","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539733","doi":"https://doi.org/10.1145/3746027.3755580"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755580","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rui Shang","orcid":"https://orcid.org/0009-0006-3325-5415"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Shang","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0009-0006-3325-5415","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343854","display_name":"Min Liu","orcid":"https://orcid.org/0000-0001-6406-4896"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Liu","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0001-6406-4896","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683380","display_name":"Xueping Wang","orcid":"https://orcid.org/0000-0003-4862-8975"},"institutions":[{"id":"https://openalex.org/I173759888","display_name":"Hunan Normal University","ror":"https://ror.org/053w1zy07","country_code":"CN","type":"education","lineage":["https://openalex.org/I173759888"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueping Wang","raw_affiliation_strings":["College of Information Science and Engineering at Hunan Normal University, Hunan Normal University, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0003-4862-8975","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering at Hunan Normal University, Hunan Normal University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I173759888"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010816880","display_name":"\u5143 \u6e21\u8fba","orcid":"https://orcid.org/0000-0003-3995-4402"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Bian","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0003-3995-4402","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113278407","display_name":"Yaonan Wang","orcid":"https://orcid.org/0009-0004-5365-6254"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaonan Wang","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0009-0004-5365-6254","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Hunan University, Changsha, Hunan, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6213","last_page":"6222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6491000056266785},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5831999778747559},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.5738000273704529},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5515999794006348},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5390999913215637},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5153999924659729},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.413100004196167},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.4059999883174896},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4025000035762787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101000189781189},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6491000056266785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5972999930381775},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5831999778747559},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.5738000273704529},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5153999924659729},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4025000035762787},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.34310001134872437},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C33222762","wikidata":"https://www.wikidata.org/wiki/Q321119","display_name":"Identity function","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2773999869823456},{"id":"https://openalex.org/C2779151265","wikidata":"https://www.wikidata.org/wiki/Q1156791","display_name":"Copying","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755580","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5877305068","display_name":null,"funder_award_id":"62425305, 62221002 and 62203168","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1982925187","https://openalex.org/W2204750386","https://openalex.org/W2585635281","https://openalex.org/W2724213014","https://openalex.org/W2962858109","https://openalex.org/W2963047834","https://openalex.org/W2964304299","https://openalex.org/W2981393440","https://openalex.org/W2984145721","https://openalex.org/W3034580371","https://openalex.org/W3035539956","https://openalex.org/W3044438666","https://openalex.org/W3195399086","https://openalex.org/W3198377975","https://openalex.org/W3217163153","https://openalex.org/W4200635168","https://openalex.org/W4285295127","https://openalex.org/W4312361652","https://openalex.org/W4387968796","https://openalex.org/W4391467966","https://openalex.org/W4406857548"],"related_works":[],"abstract_inverted_index":{"Vision-language":[0],"models":[1],"like":[2],"CLIP":[3],"have":[4],"revolutionized":[5],"person":[6],"re-identification":[7],"(ReID)":[8],"by":[9],"enabling":[10],"cross-modal":[11],"semantic":[12,27,134],"alignment.":[13],"However,":[14],"most":[15],"of":[16,96,159],"the":[17,94,160,166,181],"existing":[18],"CLIP-based":[19],"ReID":[20],"methods":[21],"suffer":[22],"from":[23],"a":[24,38,66,78],"critical":[25],"limitation:":[26],"entanglement,":[28],"where":[29],"identity":[30,76],"and":[31,99,120,176],"attribute":[32,121],"features":[33,98],"are":[34,123],"indiscriminately":[35],"compressed":[36],"into":[37,125],"single,":[39],"undifferentiated":[40],"token":[41],"representation.":[42],"This":[43],"oversight":[44],"fails":[45],"to":[46,152],"account":[47],"for":[48],"their":[49],"inherently":[50],"distinct":[51,126],"roles":[52],"in":[53],"characterizing":[54],"individuals.To":[55],"address":[56],"this":[57,141],"limitation,":[58],"we":[59],"propose":[60],"an":[61],"Identity-Attribute-Decoupled":[62],"Tokenization":[63],"(IADT)":[64],"method,":[65],"hierarchical":[67,111],"framework":[68],"with":[69,191],"two":[70],"synergistic":[71],"components:Subject-oriented":[72],"tokens":[73,88],"that":[74,89],"model":[75],"through":[77,93,136],"cross-modality":[79],"feature":[80,138],"inverse":[81],"mapping":[82],"paradigm,":[83],"preserving":[84],"invariant":[85],"biometric":[86],"features;Attribute-aware":[87],"capture":[90],"localized":[91],"characteristics":[92],"cross-interaction":[95],"local":[97],"learnable":[100],"prototype":[101],"vectors,":[102],"dynamically":[103],"focusing":[104],"on":[105,165],"discriminative":[106],"regions":[107],"without":[108],"manual":[109],"supervision.The":[110],"tokenization":[112],"enables":[113],"disentangled":[114],"yet":[115],"complementary":[116],"representation":[117],"learning:":[118],"Identity":[119],"semantics":[122],"encoded":[124],"embedding":[127],"subspaces,":[128],"while":[129],"cross-token":[130],"contrastive":[131],"learning":[132],"establishes":[133],"reinforcement":[135],"attention-guided":[137],"interaction.":[139],"Crucially,":[140],"process":[142],"does":[143],"not":[144],"require":[145],"part-level":[146],"annotations,":[147],"making":[148],"it":[149,185],"directly":[150],"applicable":[151],"real-world":[153],"deployment.":[154],"Extensive":[155],"experiments":[156],"validate":[157],"effectiveness":[158],"proposed":[161],"method.":[162],"For":[163,180],"example,":[164],"Market-1501":[167],"dataset,":[168],"IADT":[169],"achieves":[170],"97.1%":[171],"mAP":[172,188],"(+2.5%":[173],"over":[174],"SOTA)":[175],"98.2%":[177],"Rank-1":[178,193],"accuracy.":[179],"challenging":[182],"MSMT":[183],"benchmark,":[184],"attains":[186],"88.9%":[187],"(+1.7%":[189],"improvement)":[190],"93.1%":[192],"accuracy,":[194],"demonstrating":[195],"consistent":[196],"superiority.":[197],"The":[198],"code":[199],"will":[200],"be":[201],"available":[202],"at":[203],"https://github.com/llraay/IADT.":[204]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}
