{"id":"https://openalex.org/W4415310047","doi":"https://doi.org/10.1109/iccv51701.2025.01176","title":"Weakly Supervised Visible-Infrared Person Re-Identification via Heterogeneous Expert Collaborative Consistency Learning","display_name":"Weakly Supervised Visible-Infrared Person Re-Identification via Heterogeneous Expert Collaborative Consistency Learning","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415310047","doi":"https://doi.org/10.1109/iccv51701.2025.01176"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.12942","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100782178","display_name":"Yafei Zhang","orcid":"https://orcid.org/0000-0003-4594-186X"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yafei Zhang","raw_affiliation_strings":["Kunming University of Science and Technology,Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112185861","display_name":"Lingqi Kong","orcid":"https://orcid.org/0009-0000-2626-2234"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingqi Kong","raw_affiliation_strings":["Kunming University of Science and Technology,Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080535168","display_name":"Huafeng Li","orcid":"https://orcid.org/0000-0003-2462-6174"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huafeng Li","raw_affiliation_strings":["Kunming University of Science and Technology,Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017617923","display_name":"Jie Wen","orcid":"https://orcid.org/0000-0001-9554-2379"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wen","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology,Shenzhen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology,Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]}],"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":"12659","last_page":"12669"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"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":0.9958999752998352,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9225000143051147,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9186999797821045,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7239999771118164},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.652999997138977},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4765999913215637},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.36149999499320984},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3476000130176544},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.3151000142097473}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7239999771118164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694599986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6571999788284302},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.595300018787384},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4765999913215637},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2702000141143799},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2687999904155731}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.12942","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.12942","pdf_url":"https://arxiv.org/pdf/2507.12942","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":"doi:10.48550/arxiv.2507.12942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.12942","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.12942","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.12942","pdf_url":"https://arxiv.org/pdf/2507.12942","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":[],"awards":[{"id":"https://openalex.org/G2808707495","display_name":null,"funder_award_id":"62276120,62161015,61966021","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0,39,85,105],"reduce":[1],"the":[2,41,97,102,124,137,143,162,165],"reliance":[3],"of":[4,43,99,164],"visible-infrared":[5],"person":[6,21],"re-identification":[7],"(ReID)":[8],"models":[9],"on":[10,47,157],"labeled":[11,74],"cross-modal":[12,20,34,45,63,87,112,129,152],"samples,":[13,88],"this":[14],"paper":[15],"explores":[16],"a":[17,52,67,111],"weakly":[18,68],"supervised":[19,69],"ReID":[22],"method":[23],"that":[24,116],"uses":[25],"only":[26],"single-modal":[27],"sample":[28],"identity":[29,35,64,130,153],"labels,":[30],"addressing":[31],"scenarios":[32],"where":[33],"labels":[36,46],"are":[37],"unavailable.":[38],"mitigate":[40],"impact":[42],"missing":[44],"model":[48],"performance,":[49],"we":[50,109],"propose":[51],"heterogeneous":[53,94],"expert":[54],"collaborative":[55,132],"consistency":[56],"learning":[57,135],"framework,":[58],"designed":[59],"to":[60,79,146],"establish":[61],"robust":[62],"correspondences":[65],"in":[66],"manner.":[70],"This":[71],"framework":[72],"leverages":[73],"data":[75],"from":[76,101,120],"each":[77],"modality":[78],"independently":[80],"train":[81],"dedicated":[82],"classification":[83,90],"experts.":[84,122],"associate":[86],"these":[89],"experts":[91,138],"act":[92],"as":[93],"predictors,":[95],"predicting":[96],"identities":[98],"samples":[100],"other":[103],"modality.":[104],"improve":[106,151],"prediction":[107],"accuracy,":[108],"design":[110],"relationship":[113],"fusion":[114],"mechanism":[115],"effectively":[117],"integrates":[118],"predictions":[119],"different":[121],"Under":[123],"implicit":[125],"supervision":[126],"provided":[127],"by":[128],"correspondences,":[131],"and":[133,150],"consistent":[134],"among":[136],"is":[139],"encouraged,":[140],"significantly":[141],"enhancing":[142],"model's":[144],"ability":[145],"extract":[147],"modality-invariant":[148],"features":[149],"recognition.":[154],"Experimental":[155],"results":[156],"two":[158],"challenging":[159],"datasets":[160],"validate":[161],"effectiveness":[163],"proposed":[166],"method.":[167]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-18T00:00:00"}
