{"id":"https://openalex.org/W4399144459","doi":"https://doi.org/10.1145/3654823.3654883","title":"Feature Norm Regularization and Class Center Norm Standardization for Person Re-Identification","display_name":"Feature Norm Regularization and Class Center Norm Standardization for Person Re-Identification","publication_year":2024,"publication_date":"2024-03-22","ids":{"openalex":"https://openalex.org/W4399144459","doi":"https://doi.org/10.1145/3654823.3654883"},"language":"en","primary_location":{"id":"doi:10.1145/3654823.3654883","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654883","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","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/A5053014849","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-9066-3294"},"institutions":[{"id":"https://openalex.org/I4400573310","display_name":"Hangzhou City University","ror":"https://ror.org/01wck0s05","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573310"]},{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Hangzhou City University, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou City University, China","institution_ids":["https://openalex.org/I6469544","https://openalex.org/I4400573310"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015180893","display_name":"W Liu","orcid":"https://orcid.org/0009-0009-0516-7524"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Ruiqu Technology (Hangzhou) Co., Ltd, China"],"affiliations":[{"raw_affiliation_string":"Ruiqu Technology (Hangzhou) Co., Ltd, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053014849"],"corresponding_institution_ids":["https://openalex.org/I4400573310","https://openalex.org/I6469544"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06718816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"328","last_page":"334"},"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":0.9998000264167786,"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/T10828","display_name":"Biometric Identification and Security","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/norm","display_name":"Norm (philosophy)","score":0.5926145315170288},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5426580905914307},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4815230965614319},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.46924686431884766},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4581358730792999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43762093782424927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4172707796096802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3819833993911743},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36675673723220825}],"concepts":[{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5926145315170288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426580905914307},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4815230965614319},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.46924686431884766},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4581358730792999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43762093782424927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4172707796096802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3819833993911743},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36675673723220825},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654823.3654883","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3654823.3654883","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning","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":14,"referenced_works":["https://openalex.org/W2798550112","https://openalex.org/W2798590501","https://openalex.org/W2962898354","https://openalex.org/W2963289251","https://openalex.org/W2963466847","https://openalex.org/W2964140013","https://openalex.org/W2969985801","https://openalex.org/W2970390221","https://openalex.org/W2989923292","https://openalex.org/W2997738728","https://openalex.org/W3035724178","https://openalex.org/W3039204154","https://openalex.org/W3136038792","https://openalex.org/W3150864706"],"related_works":["https://openalex.org/W4254199101","https://openalex.org/W4300427796","https://openalex.org/W1670153145","https://openalex.org/W2051864124","https://openalex.org/W3023929447","https://openalex.org/W2021131614","https://openalex.org/W2364847665","https://openalex.org/W4236907339","https://openalex.org/W2005361022","https://openalex.org/W2994927414"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(ReID)":[2],"and":[3,45,115,199,206],"face":[4],"recognition":[5],"both":[6],"address":[7,60],"the":[8,12,18,31,53,57,61,64,84,97,108,112,118,126,132,141,147,169,172,179,182,187,192],"problem":[9],"of":[10,14,56,63,68,111,117,149,171,181,194,208],"calculating":[11],"similarity":[13],"two":[15,136],"images,":[16],"but":[17],"cross-entropy":[19,113],"loss":[20,95,114,127],"functions":[21],"they":[22],"use":[23],"have":[24],"significant":[25],"differences":[26,32],"in":[27,48],"form.":[28],"By":[29,123],"analyzing":[30,146],"we":[33,73,129,152],"believe":[34],"it":[35],"is":[36],"necessary":[37],"to":[38,51,82,89,106,164,204,213],"introduce":[39],"consistency":[40],"requirements":[41],"for":[42,96,190],"feature":[43,69,76,92,119],"norms":[44,47,70,163],"class-center":[46],"ReID":[49],"domain":[50],"enhance":[52],"generalization":[54],"performance":[55],"algorithm.":[58],"To":[59],"issue":[62],"changing":[65],"mean":[66,87],"value":[67,88,167],"during":[71],"training,":[72],"establish":[74],"a":[75,91,103,154],"norm":[77,93,110,120],"observer,":[78],"which":[79],"allows":[80],"us":[81],"utilize":[83],"estimated":[85],"real-time":[86],"form":[90],"regularization":[94,121],"current":[98,173],"training":[99,174],"batch.":[100,175],"We":[101],"employ":[102],"similar":[104],"method":[105,156,189],"observe":[107],"gradient":[109,133],"that":[116,131,157,207],"loss.":[122],"dynamically":[124],"adjusting":[125],"weight,":[128],"ensure":[130],"intensities":[134],"from":[135,202,211],"losses":[137],"are":[138],"aligned.":[139],"Regarding":[140],"class":[142,161],"center":[143,162],"norm,":[144],"after":[145],"necessity":[148],"its":[150],"consistency,":[151],"propose":[153],"simple":[155],"uniformly":[158],"resets":[159],"all":[160],"their":[165],"average":[166],"at":[168],"end":[170],"The":[176],"experiments":[177],"demonstrate":[178],"effectiveness":[180],"proposed":[183,188],"method.":[184],"After":[185],"applying":[186],"OSNet,":[191],"increment":[193],"mAP":[195],"on":[196],"Market1501,":[197],"CUHK03":[198],"MSMT17":[200],"ranges":[201,210],"0.8%":[203],"4.5%,":[205],"rank-1":[209],"0.2%":[212],"3.2%.":[214]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
