{"id":"https://openalex.org/W2794651663","doi":"https://doi.org/10.1109/cvpr.2018.00242","title":"Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-identification","display_name":"Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-identification","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2794651663","doi":"https://doi.org/10.1109/cvpr.2018.00242","mag":"2794651663"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2018.00242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1803.09786","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100639522","display_name":"Jingya Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jingya Wang","raw_affiliation_strings":["Queen Mary University of London","queen mary university of london"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"queen mary university of london","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028643592","display_name":"Xiatian Zhu","orcid":"https://orcid.org/0000-0002-9284-2955"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiatian Zhu","raw_affiliation_strings":["Vision Semantics Ltd","[Vision Semantics Ltd.]"],"affiliations":[{"raw_affiliation_string":"Vision Semantics Ltd","institution_ids":[]},{"raw_affiliation_string":"[Vision Semantics Ltd.]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039302902","display_name":"Shaogang Gong","orcid":"https://orcid.org/0000-0001-8156-2299"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shaogang Gong","raw_affiliation_strings":["Queen Mary University of London, London, London, GB","[Queen Mary University of London, London, London, GB]"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London, London, London, GB","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"[Queen Mary University of London, London, London, GB]","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100318314","display_name":"Wei Li","orcid":"https://orcid.org/0000-0002-9235-9429"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Queen Mary University of London","queen mary university of london"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"queen mary university of london","institution_ids":["https://openalex.org/I166337079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100639522"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":2.1247,"has_fulltext":true,"cited_by_count":35,"citation_normalized_percentile":{"value":0.90831503,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2275","last_page":"2284"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9952999949455261,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9900000095367432,"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/computer-science","display_name":"Computer science","score":0.8299592733383179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7004693746566772},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6756246089935303},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6544408798217773},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5947185754776001},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.573683500289917},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5499554872512817},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.516651451587677},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.47153550386428833},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4447501003742218},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4294120669364929},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.057993143796920776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8299592733383179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7004693746566772},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6756246089935303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6544408798217773},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5947185754776001},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.573683500289917},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5499554872512817},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.516651451587677},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.47153550386428833},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4447501003742218},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4294120669364929},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.057993143796920776},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cvpr.2018.00242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2018.00242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1803.09786","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.09786","pdf_url":"https://arxiv.org/pdf/1803.09786","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/58357","is_oa":false,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/58357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"doi:10.48550/arxiv.1803.09786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1803.09786","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:2794651663","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1803.09786","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.09786","pdf_url":"https://arxiv.org/pdf/1803.09786","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2794651663.pdf","grobid_xml":"https://content.openalex.org/works/W2794651663.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W206659046","https://openalex.org/W370501591","https://openalex.org/W1518138188","https://openalex.org/W1522301498","https://openalex.org/W1821462560","https://openalex.org/W1941498359","https://openalex.org/W1949591461","https://openalex.org/W1963702692","https://openalex.org/W1967988963","https://openalex.org/W1979260620","https://openalex.org/W1982925187","https://openalex.org/W1999478721","https://openalex.org/W2009907187","https://openalex.org/W2017257315","https://openalex.org/W2030558520","https://openalex.org/W2030801043","https://openalex.org/W2068042582","https://openalex.org/W2070784585","https://openalex.org/W2098807270","https://openalex.org/W2126791727","https://openalex.org/W2130418330","https://openalex.org/W2133257461","https://openalex.org/W2165698076","https://openalex.org/W2183341477","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2203864774","https://openalex.org/W2204750386","https://openalex.org/W2256680489","https://openalex.org/W2300840837","https://openalex.org/W2336733689","https://openalex.org/W2342611082","https://openalex.org/W2441160157","https://openalex.org/W2471048925","https://openalex.org/W2511556322","https://openalex.org/W2551835155","https://openalex.org/W2585635281","https://openalex.org/W2605911906","https://openalex.org/W2756889815","https://openalex.org/W2759735225","https://openalex.org/W2768610172","https://openalex.org/W2949605076","https://openalex.org/W2949650786","https://openalex.org/W2962706983","https://openalex.org/W2962835968","https://openalex.org/W2962926870","https://openalex.org/W2963365374","https://openalex.org/W2963721283","https://openalex.org/W2964248351","https://openalex.org/W2964289004","https://openalex.org/W3103800629","https://openalex.org/W6606760634","https://openalex.org/W6622321702","https://openalex.org/W6631178364","https://openalex.org/W6635635147","https://openalex.org/W6636160605","https://openalex.org/W6637373629","https://openalex.org/W6640937214","https://openalex.org/W6650210536","https://openalex.org/W6658349781","https://openalex.org/W6672909312","https://openalex.org/W6679718588","https://openalex.org/W6701311708","https://openalex.org/W6703244005","https://openalex.org/W6722037772","https://openalex.org/W6726612147","https://openalex.org/W6730370473","https://openalex.org/W6730389898","https://openalex.org/W6733865703","https://openalex.org/W6734650526","https://openalex.org/W6745799943","https://openalex.org/W6785238604"],"related_works":["https://openalex.org/W2963557071","https://openalex.org/W2963009244","https://openalex.org/W2963938779","https://openalex.org/W2955941942","https://openalex.org/W2900376878","https://openalex.org/W2950552715","https://openalex.org/W3175445198","https://openalex.org/W3189391247","https://openalex.org/W3126793154","https://openalex.org/W3005863149","https://openalex.org/W2987191133","https://openalex.org/W2963152148","https://openalex.org/W2441160157","https://openalex.org/W3201362247","https://openalex.org/W2953350812","https://openalex.org/W2993264241","https://openalex.org/W3163519518","https://openalex.org/W3040726071","https://openalex.org/W3212136961","https://openalex.org/W2998263413"],"abstract_inverted_index":{"Most":[0],"existing":[1,66],"person":[2,76,149],"re-identification":[3],"(re-id)":[4],"methods":[5,157],"require":[6],"supervised":[7,80],"model":[8,146],"learning":[9,57,81,98,131],"from":[10,125],"a":[11,54,69,152],"separate":[12],"large":[13,34],"set":[14],"of":[15,64,142,155],"pairwise":[16],"labelled":[17,62,122],"training":[18,123],"data":[19,124],"for":[20,40,59,75,96,113,119,147],"every":[21],"single":[22],"camera":[23,45],"pair.":[24],"This":[25],"significantly":[26],"limits":[27],"their":[28],"scalability":[29,50],"and":[30,101,166],"usability":[31],"in":[32,82,132],"real-world":[33],"scale":[35],"deployments":[36],"with":[37],"the":[38,61,83,117,126,133,140],"need":[39,118],"performing":[41],"re-id":[42,77,114,150],"across":[43],"many":[44],"views.":[46],"To":[47],"address":[48],"this":[49,143],"problem,":[51],"we":[52,87],"develop":[53],"novel":[55],"deep":[56],"method":[58],"transferring":[60],"information":[63],"an":[65,89,99],"dataset":[67],"to":[68,107],"new":[70,109,121,144],"unseen":[71],"(unlabelled)":[72],"target":[73,84,111,127,134],"domain":[74,112,128],"without":[78,116],"any":[79,108],"domain.":[85],"Specifically,":[86],"introduce":[88],"Transferable":[90],"Joint":[91],"Attribute-Identity":[92],"Deep":[93],"Learning":[94],"(TJ-AIDL)":[95],"simultaneously":[97],"attribute-semantic":[100],"identity-discriminative":[102],"feature":[103],"representation":[104],"space":[105],"transferrable":[106],"(unseen)":[110],"tasks":[115],"collecting":[120],"(i.e.":[129],"unsupervised":[130,148],"domain).":[135],"Extensive":[136],"comparative":[137],"evaluations":[138],"validate":[139],"superiority":[141],"TJ-AIDL":[145],"over":[151],"wide":[153],"range":[154],"state-of-the-art":[156],"on":[158],"four":[159],"challenging":[160],"benchmarks":[161],"including":[162],"VIPeR,":[163],"PRID,":[164],"Market-1501,":[165],"DukeMTMC-ReID.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-05T06:14:27.290980","created_date":"2025-10-10T00:00:00"}