{"id":"https://openalex.org/W7137950371","doi":"https://doi.org/10.1609/aaai.v40i15.38218","title":"Geometry-Aware Noisy Correspondence Mitigation for Cross-Modal Text-Based Person Retrieval","display_name":"Geometry-Aware Noisy Correspondence Mitigation for Cross-Modal Text-Based Person Retrieval","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137950371","doi":"https://doi.org/10.1609/aaai.v40i15.38218"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i15.38218","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38218","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38218/42180","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38218/42180","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089592676","display_name":"Xinpan Yuan","orcid":"https://orcid.org/0000-0001-9509-0755"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinpan Yuan","raw_affiliation_strings":["Hunan University of Technology"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020510485","display_name":"Shaomin Xie","orcid":"https://orcid.org/0009-0007-0181-2587"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaomin Xie","raw_affiliation_strings":["Hunan University of Technology"],"affiliations":[{"raw_affiliation_string":"Hunan University of Technology","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038781609","display_name":"Liujie Hua","orcid":"https://orcid.org/0000-0002-2756-1540"},"institutions":[{"id":"https://openalex.org/I118612203","display_name":"Hunan Police Academy","ror":"https://ror.org/02gh10772","country_code":"CN","type":"education","lineage":["https://openalex.org/I118612203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liujie Hua","raw_affiliation_strings":["Hunan Police Academy"],"affiliations":[{"raw_affiliation_string":"Hunan Police Academy","institution_ids":["https://openalex.org/I118612203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129724387","display_name":"Chengyuan Zhang","orcid":null},"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":"Chengyuan Zhang","raw_affiliation_strings":["Hunan University"],"affiliations":[{"raw_affiliation_string":"Hunan University","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129656353","display_name":"Guihu Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guihu Zhao","raw_affiliation_strings":["Central South University"],"affiliations":[{"raw_affiliation_string":"Central South University","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129645811","display_name":"Lin Yuanbo Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lin Yuanbo Wu","raw_affiliation_strings":["The University of Warwick"],"affiliations":[{"raw_affiliation_string":"The University of Warwick","institution_ids":["https://openalex.org/I39555362"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5089592676"],"corresponding_institution_ids":["https://openalex.org/I49934816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2016369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"15","first_page":"12268","last_page":"12276"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.7705000042915344,"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":0.7705000042915344,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.09319999814033508,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.03020000085234642,"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/robustness","display_name":"Robustness (evolution)","score":0.7085999846458435},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6777999997138977},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.4519999921321869},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.4332999885082245},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.42879998683929443},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42179998755455017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4059999883174896},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.36820000410079956}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7085999846458435},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6777999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521999835968018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6118000149726868},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.4519999921321869},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42179998755455017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.36820000410079956},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.3573000133037567},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.34599998593330383},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26589998602867126},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i15.38218","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38218","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38218/42180","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i15.38218","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38218","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38218/42180","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7862122654914856}],"awards":[{"id":"https://openalex.org/G174463083","display_name":null,"funder_award_id":"2024JJ9550","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2214395651","display_name":null,"funder_award_id":"2025JJ70028","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3340851556","display_name":null,"funder_award_id":"2023JJ30169","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5812059932","display_name":null,"funder_award_id":"6247216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6434207113","display_name":null,"funder_award_id":"2025JJ","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G8297447497","display_name":null,"funder_award_id":"2025JJ81178","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G8441992883","display_name":null,"funder_award_id":"62472161","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G917387035","display_name":null,"funder_award_id":"24A0401","funder_id":"https://openalex.org/F4320311213","funder_display_name":"Education Department of Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320311213","display_name":"Education Department of Hunan Province","ror":"https://ror.org/05ckg3w11"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7137950371.pdf","grobid_xml":"https://content.openalex.org/works/W7137950371.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-Based":[0],"Person":[1],"Retrieval":[2],"(TBPR)":[3],"aims":[4],"to":[5,42,49,62,113,124,163],"accurately":[6],"retrieve":[7],"target":[8],"individuals":[9],"from":[10],"large-scale":[11],"image":[12],"databases":[13],"using":[14],"only":[15],"textual":[16,56],"descriptions.":[17],"Existing":[18],"methods":[19],"typically":[20],"assume":[21],"a":[22,213,218],"ground-truth":[23],"correspondence":[24,65,72,168],"between":[25,55,74],"text":[26],"and":[27,58,76,94,120,145,156,183],"images":[28],"(i.e.,":[29],"strongly":[30],"correlated).":[31],"However,":[32],"in":[33,98,209],"real-world":[34],"scenarios,":[35],"this":[36,104],"assumption":[37],"may":[38],"not":[39],"be":[40],"able":[41],"hold":[43],"for":[44],"the":[45,71,133,142,161,166,175],"cross-modal":[46,93,117,167],"matching":[47],"due":[48],"weak":[50],"or":[51,179],"even":[52],"corrupted":[53],"correlations":[54],"descriptions":[57],"visual":[59,75],"content,":[60],"referred":[61],"as":[63],"noisy":[64,87,129,138,157],"(NC).":[66],"Such":[67],"NC":[68],"largely":[69],"disrupts":[70],"learning":[73],"semantic":[77],"modalities.":[78,188],"Though":[79],"prior":[80],"works":[81],"have":[82],"improved":[83],"single-modal":[84],"robustness":[85],"against":[86],"labels,":[88],"systematic":[89],"modeling":[90],"of":[91,177],"both":[92],"intra-modal":[95,121],"geometric":[96],"structures":[97],"TBPR":[99],"remains":[100],"limited":[101],"attention.":[102],"In":[103],"paper,":[105],"we":[106,140],"propose":[107],"Geometric":[108],"Structure":[109,143],"Consistency":[110],"Alignment":[111],"(GSCA)":[112],"TBPR,":[114],"which":[115],"leverages":[116],"cosine":[118],"similarity":[119],"nearest-neighbor":[122],"affinity":[123],"learn":[125],"visual-semantic":[126],"consistency":[127,186],"under":[128,217],"correspondence.":[130],"To":[131],"mitigate":[132],"structural":[134,185],"corruption":[135],"caused":[136],"by":[137,169,207],"pairs,":[139,172],"introduce":[141],"Refinement":[144],"Mining":[146],"(SRAM)":[147],"module.":[148],"By":[149],"partitioning":[150],"training":[151],"data":[152],"into":[153],"clean,":[154],"ambiguous,":[155],"subsets,":[158],"SRAM":[159],"enables":[160],"model":[162],"strategically":[164],"refine":[165],"mining":[170],"reliable":[171],"thus":[173],"enhancing":[174],"reliability":[176],"positive":[178],"negative":[180],"samples":[181],"discrimination":[182],"preserving":[184],"across":[187,198],"Extensive":[189],"experiments":[190],"demonstrate":[191],"that":[192],"our":[193],"method":[194],"achieves":[195],"state-of-the-art":[196],"performance":[197],"three":[199],"public":[200],"datasets.":[201],"On":[202],"CUHK-PEDES,":[203],"it":[204],"boosts":[205],"Rank-1":[206,216],"1.42%":[208],"noise-free":[210],"conditions,":[211],"sustaining":[212],"robust":[214],"74.25%":[215],"50%":[219],"noise":[220],"ratio.":[221]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-18T00:00:00"}
