{"id":"https://openalex.org/W3205254463","doi":"https://doi.org/10.1145/3474085.3475435","title":"Cluster and Scatter: A Multi-grained Active Semi-supervised Learning Framework for Scalable Person Re-identification","display_name":"Cluster and Scatter: A Multi-grained Active Semi-supervised Learning Framework for Scalable Person Re-identification","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3205254463","doi":"https://doi.org/10.1145/3474085.3475435","mag":"3205254463"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475435","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":["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/A5030896898","display_name":"Bingyu Hu","orcid":"https://orcid.org/0009-0007-6482-2803"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingyu Hu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003217535","display_name":"Zheng-Jun Zha","orcid":"https://orcid.org/0000-0003-2510-8993"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng-Jun Zha","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101827938","display_name":"Jiawei Liu","orcid":"https://orcid.org/0000-0002-4930-9637"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Liu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011313842","display_name":"Xierong Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xierong Zhu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078162380","display_name":"Hongtao Xie","orcid":"https://orcid.org/0000-0002-6249-5315"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Xie","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030896898"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.5764,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.68784314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2605","last_page":"2614"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9973999857902527,"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":0.7893859148025513},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.764128565788269},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.741762638092041},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6100272536277771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5647287368774414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5487731695175171},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.4880174696445465},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4754630923271179},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.46942976117134094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3326786756515503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893859148025513},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.764128565788269},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.741762638092041},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6100272536277771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5647287368774414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5487731695175171},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.4880174696445465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4754630923271179},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.46942976117134094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3326786756515503},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474085.3475435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475435","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1967447455","https://openalex.org/W1994757995","https://openalex.org/W2018770010","https://openalex.org/W2085989833","https://openalex.org/W2087194317","https://openalex.org/W2108598243","https://openalex.org/W2157635833","https://openalex.org/W2194775991","https://openalex.org/W2293678066","https://openalex.org/W2511791013","https://openalex.org/W2519338267","https://openalex.org/W2526833393","https://openalex.org/W2620069838","https://openalex.org/W2771641283","https://openalex.org/W2795758732","https://openalex.org/W2798991696","https://openalex.org/W2891440844","https://openalex.org/W2895094948","https://openalex.org/W2900665190","https://openalex.org/W2908027240","https://openalex.org/W2909398625","https://openalex.org/W2912152775","https://openalex.org/W2946829651","https://openalex.org/W2957037461","https://openalex.org/W2962859295","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2964344300","https://openalex.org/W2970530347","https://openalex.org/W2970832466","https://openalex.org/W2979805229","https://openalex.org/W2982673782","https://openalex.org/W2983697263","https://openalex.org/W2986514296","https://openalex.org/W2988852559","https://openalex.org/W2998388430","https://openalex.org/W3013774306","https://openalex.org/W3015703757","https://openalex.org/W3015941173","https://openalex.org/W3017068813","https://openalex.org/W3034372982","https://openalex.org/W3034527052","https://openalex.org/W3034607353","https://openalex.org/W3034727830","https://openalex.org/W3034903425","https://openalex.org/W3035070480","https://openalex.org/W3035524453","https://openalex.org/W3047597044","https://openalex.org/W3082269314","https://openalex.org/W3092938221","https://openalex.org/W3100506510","https://openalex.org/W3101397996","https://openalex.org/W3127184636","https://openalex.org/W3137251983","https://openalex.org/W3172249682","https://openalex.org/W3189423081"],"related_works":["https://openalex.org/W2264067234","https://openalex.org/W3124243301","https://openalex.org/W1571502335","https://openalex.org/W1589409554","https://openalex.org/W2759038785","https://openalex.org/W2172232600","https://openalex.org/W3123876860","https://openalex.org/W3124172198","https://openalex.org/W2142633247","https://openalex.org/W2148394657"],"abstract_inverted_index":{"Active":[0,89],"learning":[1,36,91],"has":[2],"recently":[3],"attracted":[4],"increasing":[5],"attention":[6],"in":[7,41,55,80,103,188,212,244],"the":[8,23,29,48,53,56,64,70,75,97,104,116,133,146,152,162,180,185,196,200,207,218,224,245],"task":[9],"of":[10,59,77,121,247],"person":[11,43,99],"re-identification,":[12],"due":[13,62],"to":[14,63,95,114,160,194,216],"its":[15],"unique":[16],"scalability":[17],"that":[18,232],"not":[19],"only":[20],"maximally":[21],"reduces":[22],"annotation":[24,225,250],"cost":[25],"but":[26],"also":[27],"retains":[28],"satisfying":[30],"performance.":[31],"Although":[32],"some":[33],"preliminary":[34],"active":[35],"methods":[37,243],"have":[38,47,230],"been":[39],"explored":[40],"scalable":[42,98],"re-identification":[44,100],"task,":[45],"they":[46],"following":[49],"two":[50,122],"problems:":[51],"1)":[52],"inefficiency":[54,117],"selection":[57],"process":[58],"image":[60,155],"pairs":[61,156],"huge":[65],"search":[66,134],"space,":[67],"and":[68,126,145,191,206],"2)":[69],"ineffectiveness":[71,201],"caused":[72],"by":[73,140,165],"ignoring":[74],"impact":[76],"unlabeled":[78,192],"data":[79,193],"model":[81,197,208],"training.":[82],"Considering":[83],"that,":[84],"we":[85,108,173],"propose":[86],"a":[87,111,141,166,175,237],"Multi-grained":[88],"Semi-Supervised":[90],"framework,":[92],"named":[93],"MASS,":[94],"address":[96],"problem":[101],"existing":[102],"practical":[105],"scenarios.":[106],"Specifically,":[107],"firstly":[109],"design":[110],"cluster-scatter":[112,204],"procedure":[113,205],"alleviate":[115],"problem,":[118],"which":[119,183],"consists":[120],"components:":[123],"cluster":[124,130],"step":[125,131,149],"scatter":[127,148],"step.":[128],"The":[129,203],"shrinks":[132],"space":[135],"into":[136],"individual":[137],"small":[138],"clusters":[139,164],"coarse-grained":[142],"clustering":[143],"method,":[144],"subsequent":[147],"further":[150],"mines":[151],"hard":[153],"distinguished":[154],"from":[157],"unlabelled":[158],"set":[159],"purify":[161],"learned":[163],"novel":[167],"centrality-based":[168],"adaptive":[169],"purification":[170,177],"strategy.":[171],"Afterward,":[172],"introduce":[174],"customized":[176],"loss":[178],"for":[179,198],"purified":[181],"clustering,":[182],"utilizes":[184],"complementary":[186],"information":[187],"both":[189],"labeled":[190],"optimize":[195],"solving":[199],"problem.":[202],"optimization":[209],"are":[210],"performed":[211],"an":[213],"iterative":[214],"fashion":[215],"achieve":[217,236],"promising":[219],"performance":[220,239],"while":[221],"greatly":[222],"reducing":[223],"cost.":[226],"Extensive":[227],"experimental":[228],"results":[229],"demonstrated":[231],"MASS":[233],"can":[234],"even":[235],"competitive":[238],"with":[240],"fully":[241],"supervised":[242],"case":[246],"extremely":[248],"less":[249],"requirements.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
