{"id":"https://openalex.org/W4388187787","doi":"https://doi.org/10.1145/3581783.3611980","title":"Rethinking Pseudo-Label-Based Unsupervised Person Re-ID with Hierarchical Prototype-based Graph","display_name":"Rethinking Pseudo-Label-Based Unsupervised Person Re-ID with Hierarchical Prototype-based Graph","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388187787","doi":"https://doi.org/10.1145/3581783.3611980"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611980","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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":null,"display_name":"Ben Sha","orcid":"https://orcid.org/0009-0001-2894-1035"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ben Sha","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087869694","display_name":"Baopu Li","orcid":"https://orcid.org/0000-0002-9032-3991"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baopu Li","raw_affiliation_strings":["Indepedent Researcher, Pleasonton, CA, USA"],"affiliations":[{"raw_affiliation_string":"Indepedent Researcher, Pleasonton, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021220108","display_name":"Tao Chen","orcid":"https://orcid.org/0000-0002-0779-9818"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Chen","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102013595","display_name":"Jiayuan Fan","orcid":"https://orcid.org/0000-0001-7494-0255"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayuan Fan","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044103888","display_name":"Tao Sheng","orcid":"https://orcid.org/0000-0002-8590-1232"},"institutions":[{"id":"https://openalex.org/I1342911587","display_name":"Oracle (United States)","ror":"https://ror.org/006c77m33","country_code":"US","type":"company","lineage":["https://openalex.org/I1342911587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Sheng","raw_affiliation_strings":["Oracle, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Oracle, Seattle, WA, USA","institution_ids":["https://openalex.org/I1342911587"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4315576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2090","last_page":"2100"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.8120813965797424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6498781442642212},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5746707916259766},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5250877141952515},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5243865847587585},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5237541198730469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5054595470428467},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.42589646577835083},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4237661063671112},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.41709524393081665},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41176536679267883},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11549150943756104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8120813965797424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6498781442642212},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5746707916259766},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5250877141952515},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5243865847587585},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5237541198730469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5054595470428467},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.42589646577835083},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4237661063671112},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.41709524393081665},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41176536679267883},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11549150943756104}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3611980","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2559085405","https://openalex.org/W2584637367","https://openalex.org/W2798991696","https://openalex.org/W2904427185","https://openalex.org/W2955192706","https://openalex.org/W2963000559","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2963140444","https://openalex.org/W2963289251","https://openalex.org/W2981393440","https://openalex.org/W2984145721","https://openalex.org/W2988852559","https://openalex.org/W2996695408","https://openalex.org/W2998508940","https://openalex.org/W3015031299","https://openalex.org/W3033469067","https://openalex.org/W3034607353","https://openalex.org/W3034903425","https://openalex.org/W3035038723","https://openalex.org/W3035070480","https://openalex.org/W3035402405","https://openalex.org/W3035524453","https://openalex.org/W3035539956","https://openalex.org/W3093591919","https://openalex.org/W3105077954","https://openalex.org/W3106858249","https://openalex.org/W3110389231","https://openalex.org/W3128661784","https://openalex.org/W3133783521","https://openalex.org/W3174940004","https://openalex.org/W3176033671","https://openalex.org/W3177342236","https://openalex.org/W3195315925","https://openalex.org/W3200840856","https://openalex.org/W3203755984","https://openalex.org/W3204330270","https://openalex.org/W3210967702","https://openalex.org/W4285259379","https://openalex.org/W4312666664","https://openalex.org/W4313013512","https://openalex.org/W6600135713"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W4308619659","https://openalex.org/W3213069564","https://openalex.org/W4378421684","https://openalex.org/W4294203825","https://openalex.org/W1505616161"],"abstract_inverted_index":{"Unsupervised":[0],"person":[1,23,58,70],"re-identification":[2],"(Re-ID)":[3],"aims":[4],"to":[5,20,68,100,138],"match":[6],"individuals":[7],"without":[8],"manual":[9],"annotations.":[10],"However,":[11],"existing":[12],"methods":[13],"often":[14],"struggle":[15],"with":[16,79,134],"intra-class":[17,112],"variations":[18],"due":[19],"differences":[21,113],"in":[22],"poses":[24,75],"and":[25,31,76,125],"camera":[26,77],"styles":[27],"such":[28],"as":[29,89],"resolution":[30],"environment":[32],"information.":[33],"Additionally,":[34],"clustering":[35],"may":[36],"produce":[37],"incorrect":[38],"pseudo-labels,":[39],"compounding":[40],"the":[41,84,102,109,121,135,140],"issue.":[42],"To":[43],"address":[44],"these":[45],"challenges,":[46],"we":[47,160],"propose":[48],"a":[49,63,90,95],"novel":[50],"hierarchical":[51,64,96],"prototype-based":[52,65,131],"graph":[53,66,81,132],"network":[54,137],"(HPG-Net)":[55],"for":[56],"unsupervised":[57],"Re-ID.":[59],"Our":[60],"approach":[61],"uses":[62],"structure":[67],"describe":[69],"images":[71],"by":[72,115,144],"attributes":[73],"of":[74,86,111,128],"styles,":[78],"each":[80,106,126],"node":[82],"representing":[83],"average":[85],"image":[87],"features":[88],"prototype.":[91],"We":[92,118],"then":[93],"apply":[94],"contrastive":[97],"learning":[98,104],"module":[99],"enhance":[101],"feature":[103],"at":[105],"level,":[107],"reducing":[108],"impact":[110],"caused":[114,143],"extraneous":[116],"attributes.":[117],"also":[119],"calculate":[120],"similarity":[122],"between":[123],"samples":[124],"level":[127],"prototypes,":[129],"maintaining":[130],"consistency":[133],"mean-teacher":[136],"mitigate":[139],"accumulation":[141],"errors":[142],"pseudo-labels.":[145],"Experimental":[146],"results":[147],"on":[148,164],"three":[149],"benchmarks":[150],"show":[151],"that":[152],"our":[153],"method":[154],"outperforms":[155],"state-of-the-art":[156],"(SOTA)":[157],"works.":[158],"Moreover,":[159],"achieve":[161],"promising":[162],"performance":[163],"an":[165],"occluded":[166],"dataset.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}