{"id":"https://openalex.org/W3016023295","doi":"https://doi.org/10.1109/icassp40776.2020.9053719","title":"Unsupervised Person Re-Identification Using Multi-Branch Feature Compensation Network and Link-Based Cluster Dissimilarity Metric","display_name":"Unsupervised Person Re-Identification Using Multi-Branch Feature Compensation Network and Link-Based Cluster Dissimilarity Metric","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016023295","doi":"https://doi.org/10.1109/icassp40776.2020.9053719","mag":"3016023295"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5054328783","display_name":"Lin Pan","orcid":"https://orcid.org/0000-0001-5074-7661"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Pan","raw_affiliation_strings":["Peking University,Communication and Information Security Lab,China","Communication and Information Security Lab, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Communication and Information Security Lab,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Communication and Information Security Lab, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017490346","display_name":"Gege Qi","orcid":"https://orcid.org/0000-0002-0032-6786"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gege Qi","raw_affiliation_strings":["Peking University,Communication and Information Security Lab,China","Communication and Information Security Lab, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Communication and Information Security Lab,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Communication and Information Security Lab, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021302591","display_name":"Biao Guo","orcid":"https://orcid.org/0000-0002-4366-0848"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Guo","raw_affiliation_strings":["Peking University,Communication and Information Security Lab,China","Communication and Information Security Lab, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Communication and Information Security Lab,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Communication and Information Security Lab, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Peking University,Communication and Information Security Lab,China","Communication and Information Security Lab, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Communication and Information Security Lab,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Communication and Information Security Lab, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4302","last_page":"4306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/computer-science","display_name":"Computer science","score":0.7720219492912292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6274593472480774},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6174299716949463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5957527756690979},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5750576853752136},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5630745887756348},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5385801196098328},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.524160623550415},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.48548415303230286},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.47877323627471924},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.4570363759994507},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4536820948123932},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.4402257800102234},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4298310875892639},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42189139127731323},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4163089990615845}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7720219492912292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6274593472480774},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6174299716949463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5957527756690979},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5750576853752136},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5630745887756348},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5385801196098328},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.524160623550415},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.48548415303230286},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.47877323627471924},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4570363759994507},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4536820948123932},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.4402257800102234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4298310875892639},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42189139127731323},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4163089990615845},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1948751323","https://openalex.org/W2097117768","https://openalex.org/W2204750386","https://openalex.org/W2337897552","https://openalex.org/W2441160157","https://openalex.org/W2584637367","https://openalex.org/W2778652957","https://openalex.org/W2798329462","https://openalex.org/W2799185441","https://openalex.org/W2888819616","https://openalex.org/W2891440844","https://openalex.org/W2895589658","https://openalex.org/W2904427185","https://openalex.org/W2953214814","https://openalex.org/W2962926870","https://openalex.org/W2962992847","https://openalex.org/W2963000559","https://openalex.org/W2963152148","https://openalex.org/W2963180826","https://openalex.org/W2963557071","https://openalex.org/W2963574614","https://openalex.org/W2963721283","https://openalex.org/W2963975998","https://openalex.org/W2963989829","https://openalex.org/W6718643136","https://openalex.org/W6754783249","https://openalex.org/W6754906984"],"related_works":["https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W4308619659","https://openalex.org/W4309346246","https://openalex.org/W3213069564","https://openalex.org/W4378421684","https://openalex.org/W4294203825","https://openalex.org/W1505616161"],"abstract_inverted_index":{"Feature":[0,52],"extraction":[1],"and":[2,21,41,68,123,130],"label":[3,79],"estimation":[4,80],"are":[5,66,106],"critical":[6],"in":[7,28,47,58],"unsupervised":[8,115],"person":[9],"re-identification":[10],"(re-ID).":[11],"Most":[12],"previous":[13],"works":[14],"focus":[15],"on":[16,85,120],"acquiring":[17],"high-layer":[18,71],"semantic":[19],"features":[20,36,65],"reckon":[22],"without":[23],"the":[24,29,34,60,98,128],"lower-layer":[25,64],"details":[26],"lost":[27],"learning":[30],"process,":[31],"which":[32,59],"causes":[33],"extracted":[35],"to":[37,76,96,113],"be":[38],"less":[39],"comprehensive":[40],"may":[42],"degrade":[43],"re-ID":[44,116],"performance.":[45,117],"Therefore":[46],"this":[48],"paper,":[49],"a":[50,88,110],"Multi-branch":[51],"Compensation":[53],"Network":[54],"(MFC-Net)":[55],"is":[56,94],"developed":[57],"significant":[61],"parts":[62],"of":[63,132],"learned":[67],"fused":[69],"with":[70],"feature":[72],"as":[73,109],"compensation.":[74],"Moreover,":[75],"accurately":[77],"conduct":[78],"through":[81],"applying":[82],"hierarchical":[83],"clustering":[84],"individual":[86],"samples,":[87],"Link-based":[89],"Cluster":[90],"Dissimilarity":[91],"Metric":[92],"(LCDM)":[93],"proposed":[95],"discover":[97],"inner":[99],"correlation":[100],"between":[101],"clusters.":[102],"These":[103],"two":[104],"methods":[105],"later":[107],"integrated":[108],"MFC-LCDM":[111],"scheme":[112],"improve":[114],"Extensive":[118],"experiments":[119],"large-scale":[121],"image-based":[122],"video-based":[124],"datasets":[125],"ulteriorly":[126],"demonstrate":[127],"superiority":[129],"effectiveness":[131],"MFC-LCDM.":[133]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}