{"id":"https://openalex.org/W3205336556","doi":"https://doi.org/10.1145/3474085.3475296","title":"MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification","display_name":"MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3205336556","doi":"https://doi.org/10.1145/3474085.3475296","mag":"3205336556"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475296","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th 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/2110.05886","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yiming Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Wu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xintian Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xintian Wu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Li","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jian Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Tian","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":2.0701,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.89091151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1571","last_page":"1580"},"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/T11448","display_name":"Face recognition and analysis","score":0.9887999892234802,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9851999878883362,"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/metadata","display_name":"Metadata","score":0.7727000117301941},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.7620000243186951},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5916000008583069},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5842999815940857},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5656999945640564},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5048999786376953},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4715000092983246},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.39340001344680786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789900004863739},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7727000117301941},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7620000243186951},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5916000008583069},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5842999815940857},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5656999945640564},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5048999786376953},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4690000116825104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.414900004863739},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3727000057697296},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30090001225471497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3474085.3475296","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2110.05886","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.05886","pdf_url":"https://arxiv.org/pdf/2110.05886","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:2110.05886","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.05886","pdf_url":"https://arxiv.org/pdf/2110.05886","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":[{"id":"https://openalex.org/G8036107462","display_name":null,"funder_award_id":"2020AAA0107400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1989889610","https://openalex.org/W2515904052","https://openalex.org/W2584637367","https://openalex.org/W2585635281","https://openalex.org/W2784163702","https://openalex.org/W2795758732","https://openalex.org/W2896016251","https://openalex.org/W2904427185","https://openalex.org/W2932399282","https://openalex.org/W2962859295","https://openalex.org/W2962996864","https://openalex.org/W2963000559","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2963842104","https://openalex.org/W2963852441","https://openalex.org/W2963975998","https://openalex.org/W2967515867","https://openalex.org/W2971612271","https://openalex.org/W2988852559","https://openalex.org/W2990827756","https://openalex.org/W2997114618","https://openalex.org/W2997563949","https://openalex.org/W2998508940","https://openalex.org/W2999929549","https://openalex.org/W3000723049","https://openalex.org/W3015031299","https://openalex.org/W3034236897","https://openalex.org/W3034527052","https://openalex.org/W3034607353","https://openalex.org/W3034727830","https://openalex.org/W3034903425","https://openalex.org/W3035014997","https://openalex.org/W3035070480","https://openalex.org/W3035402405","https://openalex.org/W3035486808","https://openalex.org/W3035909655","https://openalex.org/W3037448869","https://openalex.org/W3040483885","https://openalex.org/W3092883857","https://openalex.org/W3103633674","https://openalex.org/W3108381568","https://openalex.org/W3120798330","https://openalex.org/W3127196078","https://openalex.org/W3174940004","https://openalex.org/W4302313152"],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,76,88,151],"challenging":[2],"task,":[3],"unsupervised":[4,78],"person":[5,79],"ReID":[6,66,80,131],"aims":[7],"to":[8,86,127,155],"match":[9],"the":[10,30,45,98,108,120,122,130,136,141,145,158,171,174,178],"same":[11],"identity":[12],"with":[13],"query":[14],"images":[15],"which":[16,105],"does":[17],"not":[18],"require":[19],"any":[20],"labeled":[21],"information.":[22],"In":[23,44,96],"general,":[24],"most":[25],"existing":[26],"approaches":[27],"focus":[28],"on":[29,119,167],"visual":[31],"cues":[32],"only,":[33],"leaving":[34],"potentially":[35],"valuable":[36],"auxiliary":[37],"metadata":[38,49],"information":[39,85],"(e.g.,":[40],"spatio-temporal":[41],"context)":[42],"unexplored.":[43],"real":[46],"world,":[47],"such":[48,133],"is":[50,100,125],"normally":[51],"available":[52],"alongside":[53],"captured":[54],"images,":[55],"and":[56,93],"thus":[57],"plays":[58],"an":[59,162],"important":[60],"role":[61],"in":[62,71,161],"separating":[63],"several":[64],"hard":[65],"matches.":[67],"With":[68],"this":[69],"motivation":[70],"mind,":[72],"we":[73,148],"propose":[74],"MGH,":[75],"novel":[77],"approach":[81,124,176],"that":[82],"uses":[83],"meta":[84],"construct":[87],"hypergraph":[89,99],"for":[90],"feature":[91],"learning":[92],"label":[94,117],"refinement.":[95],"principle,":[97],"composed":[101],"of":[102,116,173],"camera-topology-aware":[103],"hyperedges,":[104],"can":[106],"model":[107],"heterogeneous":[109],"data":[110],"correlations":[111],"across":[112],"cameras.":[113],"Taking":[114],"advantage":[115],"propagation":[118],"hypergraph,":[121],"proposed":[123,175],"able":[126],"effectively":[128],"refine":[129],"results,":[132,147],"as":[134],"correcting":[135],"wrong":[137],"labels":[138],"or":[139],"smoothing":[140],"noisy":[142],"labels.":[143],"Given":[144],"refined":[146],"further":[149],"present":[150],"memory-based":[152],"listwise":[153],"loss":[154],"directly":[156],"optimize":[157],"average":[159],"precision":[160],"approximate":[163],"manner.":[164],"Extensive":[165],"experiments":[166],"three":[168],"benchmarks":[169],"demonstrate":[170],"effectiveness":[172],"against":[177],"state-of-the-art.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2021-10-25T00:00:00"}