{"id":"https://openalex.org/W3080411117","doi":"https://doi.org/10.1145/3394171.3413814","title":"Performance Optimization of Federated Person Re-identification via Benchmark Analysis","display_name":"Performance Optimization of Federated Person Re-identification via Benchmark Analysis","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3080411117","doi":"https://doi.org/10.1145/3394171.3413814","mag":"3080411117"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413814","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.11560","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Weiming Zhuang","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Weiming Zhuang","raw_affiliation_strings":["Nanyang Technological University &amp; SenseTime Research, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University &amp; SenseTime Research, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yonggang Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yonggang Wen","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xuesen Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesen Zhang","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xin Gan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Gan","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Daiying Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daiying Yin","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dongzhan Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongzhan Zhou","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuai Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhang","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shuai Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Yi","raw_affiliation_strings":["SenseTime Research, China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, China, China","institution_ids":["https://openalex.org/I4210128910"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":4.6094,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.95920767,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"955","last_page":"963"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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":0.9990000128746033,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.998199999332428,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8562999963760376},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.576200008392334},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5393000245094299},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4399999976158142},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40700000524520874},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.384799987077713}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.864799976348877},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8562999963760376},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.576200008392334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5515999794006348},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5393000245094299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4887999892234802},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40700000524520874},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3628000020980835},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2809999883174896},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.26969999074935913}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3394171.3413814","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2008.11560","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.11560","pdf_url":"https://arxiv.org/pdf/2008.11560","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.11560","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.11560","pdf_url":"https://arxiv.org/pdf/2008.11560","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1518138188","https://openalex.org/W1596233070","https://openalex.org/W2070784585","https://openalex.org/W2526833393","https://openalex.org/W2585635281","https://openalex.org/W2766165758","https://openalex.org/W2896234850","https://openalex.org/W2946666127","https://openalex.org/W2957037461","https://openalex.org/W2994144272","https://openalex.org/W3021654819"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"learning":[1,6,35,238],"is":[2],"a":[3,10,55,161,202],"privacy-preserving":[4],"machine":[5],"technique":[7],"that":[8,101,208,224],"learns":[9],"shared":[11],"model":[12,140,174,194],"across":[13],"decentralized":[14],"clients.":[15],"It":[16,118],"can":[17,211],"alleviate":[18],"privacy":[19],"concerns":[20],"of":[21,62,67,123,132,173,236],"personal":[22],"re-identification,":[23],"an":[24,91],"important":[25],"computer":[26,241],"vision":[27,242],"task.":[28],"In":[29],"this":[30],"work,":[31],"we":[32,147,159,186],"implement":[33],"federated":[34,87,93,237],"to":[36,58,78,164,170,190,231],"person":[37],"re-identification":[38],"(FedReID)":[39],"and":[40,89,142],"optimize":[41],"its":[42],"performance":[43,61,112,131,218],"affected":[44],"by":[45,106,136],"statistical":[46],"heterogeneity":[47],"in":[48,83,116,139,144,176,178,244],"the":[49,60,80,102,107,121,126,155,167,171,192,229,234],"real-world":[50,127,245],"scenario.":[51],"We":[52,222],"first":[53],"construct":[54],"new":[56,162],"benchmark":[57,65,98],"investigate":[59],"FedReID.":[63,96,117],"This":[64],"consists":[66],"(1)":[68,152],"nine":[69],"datasets":[70,134],"with":[71,195,216],"different":[72,76],"volumes":[73],"sourced":[74],"from":[75,198],"domains":[77],"simulate":[79],"heterogeneous":[81],"situation":[82],"reality,":[84],"(2)":[85,182],"two":[86,149],"scenarios,":[88],"(3)":[90],"enhanced":[92],"algorithm":[94],"for":[95],"The":[97],"analysis":[99],"shows":[100],"client-edge-cloud":[103],"architecture,":[104],"represented":[105],"federated-by-dataset":[108],"scenario,":[109,128],"has":[110],"better":[111,214],"than":[113],"client-server":[114],"architecture":[115],"also":[119],"reveals":[120],"bottlenecks":[122],"FedReID":[124],"under":[125],"including":[129],"poor":[130],"large":[133],"caused":[135],"unbalanced":[137,156],"weights":[138,168],"aggregation":[141],"challenges":[143],"convergence.":[145],"Then":[146],"propose":[148,160],"optimization":[150],"methods:":[151],"To":[153,183],"address":[154],"weight":[157],"problem,":[158],"method":[163],"dynamically":[165],"change":[166],"according":[169],"scale":[172],"changes":[175],"clients":[177],"each":[179],"training":[180],"round;":[181],"facilitate":[184],"convergence,":[185],"adopt":[187],"knowledge":[188,196],"distillation":[189],"refine":[191],"server":[193],"generated":[197],"client":[199],"models":[200],"on":[201,219,239],"public":[203],"dataset.":[204],"Experiment":[205],"results":[206],"demonstrate":[207],"our":[209,225],"strategies":[210],"achieve":[212],"much":[213],"convergence":[215],"superior":[217],"all":[220],"datasets.":[221],"believe":[223],"work":[226],"will":[227],"inspire":[228],"community":[230],"further":[232],"explore":[233],"implementation":[235],"more":[240],"tasks":[243],"scenarios.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":10}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2020-09-01T00:00:00"}
