{"id":"https://openalex.org/W4304083188","doi":"https://doi.org/10.1145/3503161.3548198","title":"Augmented Dual-Contrastive Aggregation Learning for Unsupervised Visible-Infrared Person Re-Identification","display_name":"Augmented Dual-Contrastive Aggregation Learning for Unsupervised Visible-Infrared Person Re-Identification","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304083188","doi":"https://doi.org/10.1145/3503161.3548198"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548198","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548198","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th 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":"https://openalex.org/A5100778644","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0003-0329-9346"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008999954","display_name":"Mang Ye","orcid":"https://orcid.org/0000-0003-3989-7655"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mang Ye","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450249","display_name":"Jun Chen","orcid":"https://orcid.org/0000-0003-1376-0167"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chen","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103206010","display_name":"Zesen Wu","orcid":"https://orcid.org/0000-0002-6094-6506"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zesen Wu","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":102,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2843","last_page":"2851"},"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":0.9821000099182129,"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":0.9718000292778015,"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/modality","display_name":"Modality (human\u2013computer interaction)","score":0.788087785243988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7603704929351807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6381229162216187},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5133327841758728},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5062012076377869},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45079731941223145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3697294592857361},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33989524841308594}],"concepts":[{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.788087785243988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7603704929351807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6381229162216187},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5133327841758728},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5062012076377869},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45079731941223145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3697294592857361},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33989524841308594},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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":1,"locations":[{"id":"doi:10.1145/3503161.3548198","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548198","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1906374873","https://openalex.org/W2187089797","https://openalex.org/W2204750386","https://openalex.org/W2761121566","https://openalex.org/W2768166594","https://openalex.org/W2896016251","https://openalex.org/W2904427185","https://openalex.org/W2954773727","https://openalex.org/W2962859295","https://openalex.org/W2963597983","https://openalex.org/W2963975998","https://openalex.org/W2970390221","https://openalex.org/W2982026851","https://openalex.org/W2985033611","https://openalex.org/W2997877744","https://openalex.org/W2998792609","https://openalex.org/W3033235266","https://openalex.org/W3034494316","https://openalex.org/W3034519219","https://openalex.org/W3035402405","https://openalex.org/W3035673257","https://openalex.org/W3107848599","https://openalex.org/W3108381568","https://openalex.org/W3120798330","https://openalex.org/W3173203577","https://openalex.org/W3173902027","https://openalex.org/W3176033671","https://openalex.org/W3177342236","https://openalex.org/W3185904166","https://openalex.org/W3202788649","https://openalex.org/W3207576380","https://openalex.org/W3207905476","https://openalex.org/W4299653752"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2018871932","https://openalex.org/W641279757","https://openalex.org/W370975646","https://openalex.org/W1670566515","https://openalex.org/W4242022592","https://openalex.org/W596972243","https://openalex.org/W2149537132"],"abstract_inverted_index":{"Visible":[0],"infrared":[1,11,55],"person":[2,48,107],"re-identification":[3,56],"(VI-ReID)":[4],"aims":[5],"at":[6,136,180],"searching":[7],"out":[8],"the":[9,44,51,58,105,137,142,148],"corresponding":[10,133],"(visible)":[12],"images":[13],"from":[14],"a":[15,83,92,116],"gallery":[16],"set":[17],"captured":[18],"by":[19],"other":[20],"spectrum":[21],"cameras.":[22],"Recent":[23],"works":[24],"mainly":[25],"focus":[26],"on":[27,147],"supervised":[28,170],"VI-ReID":[29,173],"methods":[30,162],"that":[31,141,154],"require":[32],"plenty":[33],"of":[34],"cross-modality":[35,60,68,112,117],"(visible-infrared)":[36],"identity":[37],"labels":[38,69],"which":[39],"are":[40],"more":[41],"expensive":[42],"than":[43],"annotations":[45],"in":[46,65],"single-modality":[47],"ReID.":[49],"For":[50],"unsupervised":[52,161],"learning":[53,71,89,95],"visible":[54],"(USL-VI-ReID),":[57],"large":[59],"discrepancies":[61],"lead":[62],"to":[63,103,124,174],"difficulties":[64],"generating":[66],"reliable":[67],"and":[70,130,166],"modality-invariant":[72],"features":[73,135],"without":[74],"any":[75],"annotations.":[76],"To":[77,109],"address":[78],"this":[79],"problem,":[80],"we":[81,114],"propose":[82],"novel":[84],"Augmented":[85],"Dual-Contrastive":[86],"Aggregation":[87],"(ADCA)":[88],"framework.":[90],"Specifically,":[91],"dual-path":[93],"contrastive":[94],"framework":[96],"with":[97,121],"two":[98],"modality-specific":[99],"memories":[100],"is":[101,144,178],"proposed":[102,156],"learn":[104],"intra-modality":[106],"representation.":[108],"associate":[110],"positive":[111,128],"identities,":[113],"design":[115],"memory":[118,134],"aggregation":[119],"module":[120],"count":[122],"priority":[123],"select":[125],"highly":[126],"associated":[127],"samples,":[129],"aggregate":[131],"their":[132],"cluster":[138],"level,":[139],"ensuring":[140],"optimization":[143],"explicitly":[145],"concentrated":[146],"modality-irrelevant":[149],"perspective.":[150],"Extensive":[151],"experiments":[152],"demonstrate":[153],"our":[155],"ADCA":[157],"significantly":[158],"outperforms":[159],"existing":[160],"under":[163],"various":[164],"settings,":[165],"even":[167],"surpasses":[168],"some":[169],"counterparts,":[171],"facilitating":[172],"real-world":[175],"deployment.":[176],"Code":[177],"available":[179],"https://github.com/yangbincv/ADCA.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":18}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
