{"id":"https://openalex.org/W4402979446","doi":"https://doi.org/10.1109/icme57554.2024.10688201","title":"Unknown Instance Learning for Person Search","display_name":"Unknown Instance Learning for Person Search","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402979446","doi":"https://doi.org/10.1109/icme57554.2024.10688201"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10688201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5100306850","display_name":"Lan Yan","orcid":"https://orcid.org/0000-0001-6452-9649"},"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":true,"raw_author_name":"Lan Yan","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078793726","display_name":"Kenli Li","orcid":"https://orcid.org/0000-0002-2635-7716"},"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":"Kenli Li","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100306850"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.4949,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65197802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.970300018787384,"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":0.970300018787384,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9562000036239624,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7070782780647278},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5124176144599915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4133756160736084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7070782780647278},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124176144599915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4133756160736084}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10688201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme57554.2024.10688201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2883754639","https://openalex.org/W2884030607","https://openalex.org/W2895675617","https://openalex.org/W2931882224","https://openalex.org/W2943826729","https://openalex.org/W2963574614","https://openalex.org/W2963639915","https://openalex.org/W2963787027","https://openalex.org/W2963901085","https://openalex.org/W2990501368","https://openalex.org/W2997268173","https://openalex.org/W3014726960","https://openalex.org/W3034230918","https://openalex.org/W3034308694","https://openalex.org/W3035228163","https://openalex.org/W3170005157","https://openalex.org/W3175630131","https://openalex.org/W3176336223","https://openalex.org/W3177239166","https://openalex.org/W4312554764","https://openalex.org/W4313069218","https://openalex.org/W4386065638","https://openalex.org/W4386071491"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Although":[0],"person":[1,25,38,181],"search":[2,39,107,182],"has":[3],"achieved":[4],"great":[5],"progress":[6],"with":[7],"advanced":[8],"deep":[9],"neural":[10],"networks,":[11],"it":[12],"remains":[13],"an":[14,88],"intricate":[15],"challenge,":[16],"necessitating":[17],"a":[18,79,110,145],"concurrent":[19],"solution":[20],"to":[21,28,47,92,118,178],"pedestrian":[22],"detection":[23],"and":[24,135,152,158,167],"re-identification.":[26],"Due":[27],"the":[29,34,48,67,94,105,121,130,165,171],"difficulty":[30],"of":[31,69,98,133,173],"accurate":[32],"labeling,":[33],"current":[35],"widely":[36],"used":[37],"datasets":[40,169],"contain":[41],"numerous":[42],"unknown":[43,60,99,125],"identities":[44],"in":[45,139,176],"addition":[46],"carefully":[49],"labeled":[50],"known":[51],"ones.":[52],"However,":[53],"previous":[54],"efforts":[55],"usually":[56],"simply":[57],"utilize":[58],"these":[59],"persons":[61],"as":[62],"negative":[63],"samples,":[64],"inadvertently":[65],"disregarding":[66],"wealth":[68],"untapped":[70],"sample":[71],"information.":[72],"To":[73],"tackle":[74],"this":[75],"issue,":[76],"we":[77,143],"propose":[78],"novel":[80],"Unknown":[81],"Instance":[82,148],"Learning":[83],"(UIL)":[84],"method":[85],"that":[86],"introduces":[87],"extra":[89],"network":[90],"branch":[91],"mine":[93],"potential":[95],"identity":[96,137],"information":[97],"individuals":[100],"during":[101],"training,":[102],"apart":[103],"from":[104,124],"fundamental":[106],"branch.":[108],"Specifically,":[109],"Clustering-Based":[111],"Unknowns":[112],"Labeling":[113],"(CBUL)":[114],"mechanism":[115],"is":[116],"introduced":[117],"effectively":[119],"exploit":[120],"features":[122],"extracted":[123],"persons.":[126],"In":[127],"addition,":[128],"recognizing":[129],"distinct":[131],"roles":[132],"pseudo":[134,159],"real":[136,157],"labels":[138,160],"discriminative":[140],"feature":[141],"learning,":[142],"design":[144],"Reformative":[146],"Online":[147],"Matching":[149],"(ROIM)":[150],"loss":[151],"maintain":[153],"lookup":[154],"tables":[155],"for":[156],"separately.":[161],"Extensive":[162],"experiments":[163],"on":[164],"CUHK-SYSU":[166],"PRW":[168],"demonstrate":[170],"superiority":[172],"our":[174],"approach":[175],"comparison":[177],"other":[179],"state-of-the-art":[180],"models.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}