{"id":"https://openalex.org/W4415535621","doi":"https://doi.org/10.1145/3746027.3755549","title":"Positive Style Accumulation: A Style Screening and Continuous Utilization Framework for Federated DG-ReID","display_name":"Positive Style Accumulation: A Style Screening and Continuous Utilization Framework for Federated DG-ReID","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415535621","doi":"https://doi.org/10.1145/3746027.3755549"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755549","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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/A5100696102","display_name":"Xin Xu","orcid":"https://orcid.org/0000-0003-0748-3669"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Xu","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120130959","display_name":"Chaoyue Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoyue Ren","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735254","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-9897-1213"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018298375","display_name":"Wenke Huang","orcid":"https://orcid.org/0000-0003-4819-293X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenke Huang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778644","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0003-0329-9346"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061566111","display_name":"Zhengxin Yu","orcid":"https://orcid.org/0009-0004-1851-3493"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixi Yu","raw_affiliation_strings":["Wuhan University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103140908","display_name":"Kui Jiang","orcid":"https://orcid.org/0000-0002-4055-7503"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Jiang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100696102"],"corresponding_institution_ids":["https://openalex.org/I43922553"],"apc_list":null,"apc_paid":null,"fwci":2.4849,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91955538,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8527","last_page":"8536"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9968000054359436,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9968000054359436,"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":0.9868999719619751,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9865000247955322,"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/generalization","display_name":"Generalization","score":0.7562000155448914},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6618000268936157},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41440001130104065},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.336899995803833},{"id":"https://openalex.org/keywords/memory-model","display_name":"Memory model","score":0.3255999982357025}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7562000155448914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289999723434448},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6618000268936157},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41999998688697815},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41440001130104065},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36340001225471497},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.3255999982357025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C2781285556","wikidata":"https://www.wikidata.org/wiki/Q1820370","display_name":"Learning styles","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C2982912361","wikidata":"https://www.wikidata.org/wiki/Q1851867","display_name":"Mental model","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755549","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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":21,"referenced_works":["https://openalex.org/W2963842104","https://openalex.org/W2967515867","https://openalex.org/W3006871679","https://openalex.org/W3033112120","https://openalex.org/W3034727830","https://openalex.org/W3080411117","https://openalex.org/W3136792391","https://openalex.org/W3150864706","https://openalex.org/W3166601111","https://openalex.org/W3182158470","https://openalex.org/W3188606522","https://openalex.org/W4206982465","https://openalex.org/W4224242030","https://openalex.org/W4226017838","https://openalex.org/W4297095241","https://openalex.org/W4312361652","https://openalex.org/W4312699393","https://openalex.org/W4386066134","https://openalex.org/W4386076561","https://openalex.org/W4391848934","https://openalex.org/W4411726016"],"related_works":[],"abstract_inverted_index":{"The":[0],"Federated":[1],"Domain":[2],"Generalization":[3,113],"for":[4,119,140,272],"Person":[5],"re-identification":[6],"(FedDG-ReID)":[7],"aims":[8],"to":[9,20,42,60,71,86,123,174,192,218,231,250],"learn":[10],"a":[11,101,112,134,163,169,186],"global":[12,150],"server":[13],"model":[14,122,151],"that":[15,55,68,147,245,281],"can":[16,247],"be":[17],"effectively":[18,87,232],"generalized":[19],"source":[21,27,290],"and":[22,89,104,125,154,210,251,262,292],"target":[23,294],"domains":[24],"through":[25,38],"distributed":[26],"domain":[28,291],"data.":[29],"Existing":[30],"methods":[31,286],"mainly":[32],"improve":[33],"the":[34,46,50,61,72,92,131,149,160,177,211,234,241,260,273,289,293],"diversity":[35],"of":[36,49,196,237,265],"samples":[37],"style":[39,170],"transformation,":[40],"which":[41,268],"some":[43],"extent":[44],"enhances":[45],"generalization":[47,62,74,275],"performance":[48,75],"model.":[51],"However,":[52],"we":[53,65,99,110,167,184],"discover":[54],"not":[56],"all":[57],"styles":[58,67,146,158,179,209,214,239],"contribute":[59],"performance.":[63,276],"Therefore,":[64],"define":[66],"are":[69],"beneficial/harmful":[70],"model's":[73,274],"as":[76],"positive/negative":[77],"styles.":[78,94,129,198],"Based":[79],"on":[80,222],"this,":[81],"new":[82,238],"issues":[83],"arise:":[84],"How":[85],"screen":[88,124],"continuously":[90],"utilize":[91],"positive":[93,128,145,157,178,197,213,266],"To":[95],"solve":[96],"these":[97,156],"problems,":[98],"propose":[100,168,185],"Style":[102,116,188],"Screening":[103],"Continuous":[105],"Utilization":[106],"(SSCU)":[107],"framework.":[108],"Firstly,":[109],"design":[111],"Gain-guided":[114],"Dynamic":[115],"Memory":[117],"(GGDSM)":[118],"each":[120,141],"client":[121,220,242],"accumulate":[126],"generated":[127,208],"Specifically,":[130],"memory":[132,161,171,217],"maintains":[133],"prototype":[135],"initialized":[136],"from":[137],"raw":[138],"data":[139],"category,":[142],"then":[143],"screens":[144],"enhance":[148],"during":[152],"training,":[153],"updates":[155],"into":[159],"using":[162],"momentum-based":[164],"approach.":[165],"Meanwhile,":[166],"recognition":[172],"loss":[173],"fully":[175],"leverage":[176],"memorized":[180],"by":[181,240],"GGDSM.":[182],"Furthermore,":[183],"Collaborative":[187],"Training":[189],"(CST)":[190],"strategy":[191,228,258],"make":[193],"full":[194],"use":[195],"Unlike":[199],"traditional":[200],"learning":[201],"strategies,":[202],"our":[203,282],"approach":[204],"leverages":[205],"both":[206,288],"newly":[207],"accumulated":[212],"stored":[215],"in":[216,287],"train":[219],"models":[221],"two":[223],"distinct":[224],"branches.":[225],"This":[226],"training":[227],"is":[229,269],"designed":[230],"promote":[233],"rapid":[235],"acquisition":[236],"models,":[243],"ensuring":[244],"they":[246],"quickly":[248],"adapt":[249],"integrate":[252],"novel":[253],"stylistic":[254],"variations.":[255],"Simultaneously,":[256],"this":[257],"guarantees":[259],"continuous":[261],"thorough":[263],"utilization":[264],"styles,":[267],"highly":[270],"beneficial":[271],"Extensive":[277],"experimental":[278],"results":[279],"demonstrate":[280],"method":[283],"outperforms":[284],"existing":[285],"domain.":[295]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-25T00:00:00"}
