{"id":"https://openalex.org/W4312992815","doi":"https://doi.org/10.1109/tits.2022.3224233","title":"Pseudo Label Rectification With Joint Camera Shift Adaptation and Outlier Progressive Recycling for Unsupervised Person Re-Identification","display_name":"Pseudo Label Rectification With Joint Camera Shift Adaptation and Outlier Progressive Recycling for Unsupervised Person Re-Identification","publication_year":2022,"publication_date":"2022-12-01","ids":{"openalex":"https://openalex.org/W4312992815","doi":"https://doi.org/10.1109/tits.2022.3224233"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3224233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3224233","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","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":"https://openalex.org/A5101639578","display_name":"Mingyuan Xu","orcid":"https://orcid.org/0009-0006-2374-2957"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingyuan Xu","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085707125","display_name":"Haiyun Guo","orcid":"https://orcid.org/0000-0001-9241-6211"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyun Guo","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9241-6211","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013880628","display_name":"Yuheng Jia","orcid":"https://orcid.org/0000-0002-3907-6550"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuheng Jia","raw_affiliation_strings":["Key Laboratory of Computer Network and Information Integration, Ministry of Education, and the School of Computer Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3907-6550","affiliations":[{"raw_affiliation_string":"Key Laboratory of Computer Network and Information Integration, Ministry of Education, and the School of Computer Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040148684","display_name":"Zhitao Dai","orcid":"https://orcid.org/0000-0003-0554-689X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhitao Dai","raw_affiliation_strings":["School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058420913","display_name":"Jinqiao Wang","orcid":"https://orcid.org/0000-0002-9118-2780"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinqiao Wang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-9118-2780","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101639578"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":1.2245,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80746465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"24","issue":"3","first_page":"3395","last_page":"3406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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":0.991100013256073,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.7797856330871582},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7116618752479553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6377352476119995},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5952510833740234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.55797278881073},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5346049070358276},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.5298205018043518},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5100410580635071},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35417693853378296},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13413232564926147}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7797856330871582},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7116618752479553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6377352476119995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5952510833740234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.55797278881073},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5346049070358276},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.5298205018043518},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5100410580635071},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35417693853378296},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13413232564926147},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3224233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3224233","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G103277725","display_name":null,"funder_award_id":"62106044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3851674897","display_name":null,"funder_award_id":"62076235","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4825246002","display_name":null,"funder_award_id":"2021ZD0110403","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6808279606","display_name":null,"funder_award_id":"62002357","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7573516140","display_name":null,"funder_award_id":"BK20210221","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G8069988032","display_name":null,"funder_award_id":"62002356","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"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2108598243","https://openalex.org/W2156483112","https://openalex.org/W2187089797","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2584637367","https://openalex.org/W2795758732","https://openalex.org/W2884366600","https://openalex.org/W2953214814","https://openalex.org/W2962858109","https://openalex.org/W2962859295","https://openalex.org/W2962996864","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2963842104","https://openalex.org/W2967515867","https://openalex.org/W2971402774","https://openalex.org/W2975612241","https://openalex.org/W2984145721","https://openalex.org/W2988852559","https://openalex.org/W2995852213","https://openalex.org/W2998989269","https://openalex.org/W3003755145","https://openalex.org/W3008706867","https://openalex.org/W3034140121","https://openalex.org/W3034607353","https://openalex.org/W3034627172","https://openalex.org/W3034903425","https://openalex.org/W3035402405","https://openalex.org/W3080270785","https://openalex.org/W3095467524","https://openalex.org/W3100506510","https://openalex.org/W3103633674","https://openalex.org/W3106772544","https://openalex.org/W3106858249","https://openalex.org/W3108381568","https://openalex.org/W3110389231","https://openalex.org/W3115484111","https://openalex.org/W3126664093","https://openalex.org/W3138973758","https://openalex.org/W3157160323","https://openalex.org/W3159683145","https://openalex.org/W3174505228","https://openalex.org/W3174940004","https://openalex.org/W3176033671","https://openalex.org/W3184225461","https://openalex.org/W3189423081","https://openalex.org/W3191697454","https://openalex.org/W3194199634","https://openalex.org/W3196659278","https://openalex.org/W3201928165","https://openalex.org/W3203755984","https://openalex.org/W3204330270","https://openalex.org/W3205336556","https://openalex.org/W3206276003","https://openalex.org/W4226074212","https://openalex.org/W6631190155","https://openalex.org/W6637131181","https://openalex.org/W6771395016","https://openalex.org/W6779510507","https://openalex.org/W6782647544","https://openalex.org/W6787282323","https://openalex.org/W6792400148","https://openalex.org/W6800013435"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1482912984","https://openalex.org/W1457719682","https://openalex.org/W4312820490"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(re-ID)":[2],"has":[3],"many":[4],"applications":[5],"in":[6,33,83,170,179],"intelligent":[7],"transportation":[8],"systems.":[9],"Clustering-based":[10],"methods,":[11],"which":[12,66,106,167],"alternate":[13],"between":[14,58],"the":[15,23,26,50,55,61,79,89,94,128,142,157,161,164,176,184,206,209,217,238,252],"generation":[16],"of":[17,25,78,130,145,166,187,205,216,220,240],"pseudo":[18,102,131],"labels":[19,132],"via":[20],"clustering":[21,62],"and":[22,113,136,155,229,247],"optimization":[24],"feature":[27,51,158],"extractor,":[28],"have":[29],"obtained":[30],"leading":[31],"performance":[32],"unsupervised":[34,228,230],"person":[35,234],"re-ID.":[36],"But":[37],"there":[38],"are":[39,82],"still":[40],"two":[41,146],"issues":[42],"not":[43],"well":[44],"addressed:":[45],"1)":[46],"Most":[47],"methods":[48],"measure":[49],"similarity":[52,144,159],"without":[53],"considering":[54],"domain":[56,231],"shift":[57,190],"cameras,":[59],"degrading":[60],"performance.":[63],"2)":[64],"Outliers,":[65],"usually":[67],"correspond":[68],"to":[69,126,181,202,212],"hard":[70],"samples":[71,147],"with":[72,251],"large":[73,226],"discrepancy":[74],"from":[75,88,133],"other":[76],"images":[77],"identical":[80],"person,":[81],"most":[84],"cases":[85],"directly":[86],"excluded":[87],"network":[90,154,177],"training.":[91],"To":[92],"tackle":[93],"above":[95],"issues,":[96],"this":[97],"paper":[98],"proposes":[99],"a":[100,150],"plug-and-play":[101],"label":[103],"rectification":[104],"framework,":[105],"jointly":[107],"utilizes":[108],"CAmera":[109],"Shift":[110],"adapTation":[111],"module":[112],"Outlier":[114],"progressive":[115,199],"Recycling":[116],"strategy":[117,201],"(":[118],"<inline-formula":[119,241],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[120,242],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[121,243],"<tex-math":[122,244],"notation=\"LaTeX\">$CASTOR$":[123,245],"</tex-math></inline-formula>":[124,246],")":[125],"improve":[127],"quality":[129],"both":[134],"pre-clustering":[135],"post-clustering.":[137],"Specifically,":[138],"we":[139,194],"first":[140],"compute":[141],"camera":[143,152,162],"by":[148,160],"utilizing":[149],"pretrained":[151],"classification":[153],"subtract":[156],"similarity,":[163],"value":[165],"is":[168],"weighted":[169],"an":[171,197],"exponential":[172],"decay":[173],"manner":[174],"throughout":[175],"training,":[178],"order":[180],"adaptively":[182],"remedy":[183],"adverse":[185],"impact":[186],"inter-camera":[188],"distribution":[189],"upon":[191],"clustering.":[192],"Besides,":[193],"carefully":[195],"design":[196],"outlier":[198],"recycling":[200],"reassign":[203],"part":[204],"outliers":[207],"into":[208],"clustered":[210],"groups":[211],"make":[213],"full":[214],"use":[215],"useful":[218],"information":[219],"outliers.":[221],"Extensive":[222],"experiments":[223],"on":[224],"three":[225],"scale":[227],"adaptive":[232],"(UDA)":[233],"re-ID":[235],"benchmarks":[236],"validate":[237],"effectiveness":[239],"its":[248],"wide":[249],"compatibility":[250],"state-of-the-art":[253],"clustering-based":[254],"methods.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
