{"id":"https://openalex.org/W4410636850","doi":"https://doi.org/10.1145/3701716.3717652","title":"One for All: A Review of Large Pre-training Models for Re-Identification","display_name":"One for All: A Review of Large Pre-training Models for Re-Identification","publication_year":2025,"publication_date":"2025-05-08","ids":{"openalex":"https://openalex.org/W4410636850","doi":"https://doi.org/10.1145/3701716.3717652"},"language":"en","primary_location":{"id":"doi:10.1145/3701716.3717652","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717652","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717652","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"review","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717652","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060480766","display_name":"Yubing Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yubing Sun","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039546706","display_name":"Shuguang Dou","orcid":"https://orcid.org/0000-0003-3231-8817"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguang Dou","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101299930","display_name":"Qi Ding","orcid":"https://orcid.org/0000-0002-6754-4817"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Qi","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385631","display_name":"Yanping Li","orcid":"https://orcid.org/0000-0001-9080-0965"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanping Li","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074011980","display_name":"Jiale Zhao","orcid":"https://orcid.org/0009-0001-2805-8664"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Zhao","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064237960","display_name":"Cairong Zhao","orcid":"https://orcid.org/0000-0001-6745-9674"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cairong Zhao","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5060480766"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05773584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1581","last_page":"1585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/identification","display_name":"Identification (biology)","score":0.7091563940048218},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6357654333114624},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.46810007095336914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3771369159221649},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3204870820045471},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06062421202659607}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7091563940048218},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6357654333114624},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.46810007095336914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3771369159221649},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3204870820045471},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06062421202659607},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701716.3717652","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717652","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717652","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701716.3717652","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3717652","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3717652","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410636850.pdf","grobid_xml":"https://content.openalex.org/works/W4410636850.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W157648163","https://openalex.org/W2990138404","https://openalex.org/W2998792609","https://openalex.org/W3159481202","https://openalex.org/W3175445198","https://openalex.org/W4214736485","https://openalex.org/W4312337588","https://openalex.org/W4312532537","https://openalex.org/W4312722479","https://openalex.org/W4312760656","https://openalex.org/W4312794873","https://openalex.org/W4313188957","https://openalex.org/W4377235190","https://openalex.org/W4378373476","https://openalex.org/W4382460786","https://openalex.org/W4385764787","https://openalex.org/W4386065939","https://openalex.org/W4386066150","https://openalex.org/W4387968796","https://openalex.org/W4388145471","https://openalex.org/W4390874394","https://openalex.org/W4393153810","https://openalex.org/W4402754290","https://openalex.org/W6600075759"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(ReID)":[2],"aims":[3],"to":[4,26,87,113,156],"match":[5],"a":[6,13,44,75],"target":[7],"pedestrian":[8],"across":[9,136],"non-overlapping":[10],"camera":[11],"views,":[12],"task":[14],"that":[15],"faces":[16],"significant":[17],"challenges":[18],"such":[19,38,100],"as":[20,39,43,88,101,108],"data":[21],"dependency":[22],"and":[23,59,127,133,142,150,185],"overfitting":[24],"due":[25],"the":[27,89,123,163],"lim-":[28],"ited":[29],"availability":[30],"of":[31,78,122,125,166],"annotated":[32],"datasets.":[33],"Recently,":[34],"large":[35,79,167],"pre-training":[36,80,98,106,146,168],"models,":[37,99,107],"CLIP,":[40],"have":[41],"emerged":[42],"transformative":[45],"paradigm":[46,95],"in":[47,170,180],"visual":[48],"learning.":[49],"These":[50],"models":[51,81,169],"generate":[52],"universal":[53],"features":[54],"with":[55],"strong":[56],"discriminative":[57],"power":[58],"generalization":[60],"capabilities,":[61],"making":[62],"them":[63],"highly":[64],"suitable":[65],"for":[66,82,91,148,177],"diverse":[67],"ReID":[68,115,140,149,172],"tasks.":[69,116],"In":[70],"this":[71,181],"paper,":[72],"we":[73,85,143],"present":[74],"comprehensive":[76],"survey":[77],"ReID,":[83],"which":[84],"refer":[86],"''One":[90],"All''":[92],"approach.":[93],"This":[94],"leverages":[96],"large-scale":[97],"self-supervised":[102,145],"or":[103],"language-":[104],"image":[105],"general":[109],"feature":[110],"extractors":[111],"adaptable":[112],"multiple":[114],"We":[117],"provide":[118],"an":[119],"in-depth":[120],"analysis":[121],"strengths":[124],"CLIP":[126],"DINO":[128],"series,":[129],"summarizing":[130],"its":[131],"application":[132],"advance-":[134],"ments":[135],"six":[137],"extensively":[138],"studied":[139],"directions":[141],"review":[144],"approaches":[147],"related":[151],"tasks,":[152],"highlighting":[153],"their":[154],"ability":[155],"achieve":[157],"task-agnostic":[158],"adaptability.":[159],"Our":[160],"findings":[161],"demonstrate":[162],"immense":[164],"potential":[165],"advancing":[171],"research,":[173],"offering":[174],"valuable":[175],"insights":[176],"future":[178],"developments":[179],"field.":[182],"Relevant":[183],"datasets":[184],"documents":[186],"are":[187],"at":[188],"https://":[189],"github.com/":[190],"Vill-Lab/":[191],"Awesome-Evolving-ReID.":[192]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}