{"id":"https://openalex.org/W4292604336","doi":"https://doi.org/10.3390/s22166293","title":"Integration of Multi-Head Self-Attention and Convolution for Person Re-Identification","display_name":"Integration of Multi-Head Self-Attention and Convolution for Person Re-Identification","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4292604336","doi":"https://doi.org/10.3390/s22166293","pmid":"https://pubmed.ncbi.nlm.nih.gov/36016054"},"language":"en","primary_location":{"id":"doi:10.3390/s22166293","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22166293","pdf_url":"https://www.mdpi.com/1424-8220/22/16/6293/pdf?version=1661157182","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/16/6293/pdf?version=1661157182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101683022","display_name":"Y. Zhou","orcid":"https://orcid.org/0000-0003-4784-6794"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalei Zhou","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China"],"raw_orcid":"https://orcid.org/0000-0003-4784-6794","affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346754","display_name":"Peng Liu","orcid":"https://orcid.org/0000-0001-7267-0634"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Liu","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China","School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China","Yangzhong Intelligent Electric Research Center, North China Electric Power University, Yangzhong 212211, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Yangzhong Intelligent Electric Research Center, North China Electric Power University, Yangzhong 212211, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100711127","display_name":"Yue Cui","orcid":"https://orcid.org/0000-0002-5001-4940"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Cui","raw_affiliation_strings":["School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713869","display_name":"Chunguang Liu","orcid":"https://orcid.org/0000-0002-2304-3789"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunguang Liu","raw_affiliation_strings":["Yangzhong Intelligent Electric Research Center, North China Electric Power University, Yangzhong 212211, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yangzhong Intelligent Electric Research Center, North China Electric Power University, Yangzhong 212211, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074652742","display_name":"Wenli Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenli Duan","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100346754"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.2178,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80194462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"22","issue":"16","first_page":"6293","last_page":"6293"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9937000274658203,"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":0.782446026802063},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6383285522460938},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.589318037033081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5843580365180969},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5665696859359741},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5370568037033081},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5352191925048828},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5316308736801147},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49162083864212036},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.47233834862709045},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4697440266609192},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.440790593624115},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4149187505245209},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.24018117785453796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21621492505073547},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19081085920333862},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1886100172996521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.782446026802063},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6383285522460938},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.589318037033081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5843580365180969},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5665696859359741},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5370568037033081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5352191925048828},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5316308736801147},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49162083864212036},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.47233834862709045},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4697440266609192},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.440790593624115},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4149187505245209},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.24018117785453796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21621492505073547},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19081085920333862},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1886100172996521},{"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/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069636","descriptor_name":"Pedestrians","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22166293","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22166293","pdf_url":"https://www.mdpi.com/1424-8220/22/16/6293/pdf?version=1661157182","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36016054","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36016054","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a1cc8f2ca8084392ad3bcf8acc87d4a0","is_oa":true,"landing_page_url":"https://doaj.org/article/a1cc8f2ca8084392ad3bcf8acc87d4a0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 16, p 6293 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/16/6293/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22166293","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 16; Pages: 6293","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9414396","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9414396","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22166293","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22166293","pdf_url":"https://www.mdpi.com/1424-8220/22/16/6293/pdf?version=1661157182","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4292604336.pdf","grobid_xml":"https://content.openalex.org/works/W4292604336.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1982925187","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2432402544","https://openalex.org/W2467139031","https://openalex.org/W2511791013","https://openalex.org/W2549139847","https://openalex.org/W2584637367","https://openalex.org/W2736410039","https://openalex.org/W2768610172","https://openalex.org/W2795758732","https://openalex.org/W2924164130","https://openalex.org/W2943407549","https://openalex.org/W2954765307","https://openalex.org/W2962691289","https://openalex.org/W2962706983","https://openalex.org/W2962926870","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2963078173","https://openalex.org/W2963091558","https://openalex.org/W2963690547","https://openalex.org/W2963842104","https://openalex.org/W2963901085","https://openalex.org/W2964163358","https://openalex.org/W2964304299","https://openalex.org/W2966094134","https://openalex.org/W2968623227","https://openalex.org/W2972012950","https://openalex.org/W2979938149","https://openalex.org/W2980073905","https://openalex.org/W2987151592","https://openalex.org/W2988964414","https://openalex.org/W2989923292","https://openalex.org/W2997738728","https://openalex.org/W3034140121","https://openalex.org/W3100506510","https://openalex.org/W3100555577","https://openalex.org/W3124582122","https://openalex.org/W3130249870","https://openalex.org/W3138516171","https://openalex.org/W3143016713","https://openalex.org/W3157952798","https://openalex.org/W3172509117","https://openalex.org/W3175445198","https://openalex.org/W3175823695","https://openalex.org/W3178613577","https://openalex.org/W3193305989","https://openalex.org/W3199929423","https://openalex.org/W3205959870","https://openalex.org/W4214736485","https://openalex.org/W4225898543","https://openalex.org/W4385245566","https://openalex.org/W6684191040","https://openalex.org/W6739901393","https://openalex.org/W6762205418","https://openalex.org/W6779510507","https://openalex.org/W6794282175","https://openalex.org/W6796750486"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"is":[2,33,46,116],"essential":[3],"to":[4,37,58,103,122,133],"intelligent":[5],"video":[6],"analytics,":[7],"whose":[8],"results":[9],"affect":[10],"downstream":[11],"tasks":[12],"such":[13],"as":[14],"behavior":[15],"and":[16,154,161],"event":[17],"analysis.":[18],"However,":[19],"most":[20],"existing":[21],"models":[22],"only":[23],"consider":[24,38],"the":[25,29,79,85,105,109,119,127,138,157],"accuracy,":[26],"rather":[27],"than":[28,78],"computational":[30,106,114],"complexity,":[31],"which":[32],"also":[34],"an":[35,68,148],"aspect":[36],"in":[39,89],"practical":[40],"deployment.":[41],"We":[42,66],"note":[43],"that":[44],"self-attention":[45,102],"a":[47],"powerful":[48],"technique":[49],"for":[50,64],"representation":[51],"learning.":[52],"It":[53],"can":[54],"work":[55],"with":[56,75,91],"convolution":[57],"learn":[59],"more":[60],"discriminative":[61],"feature":[62,71],"representations":[63],"re-identification.":[65],"propose":[67],"improved":[69],"multi-scale":[70],"learning":[72],"structure,":[73],"DM-OSNet,":[74],"better":[76],"performance":[77],"original":[80,110,120],"OSNet.":[81],"Our":[82],"DM-OSNet":[83,146],"replaces":[84],"9\u00d79":[86],"convolutional":[87],"stream":[88],"OSNet":[90],"multi-head":[92,101,111],"self-attention.":[93,112],"To":[94,124],"maintain":[95],"model":[96,128],"efficiency,":[97],"we":[98,130],"use":[99,131],"double-layer":[100],"reduce":[104],"complexity":[107,115],"of":[108,150],"The":[113],"reduced":[117],"from":[118],"O((H\u00d7W)2)":[121],"O(H\u00d7W\u00d7G2).":[123],"further":[125],"improve":[126],"performance,":[129],"SpCL":[132],"perform":[134],"unsupervised":[135],"pre-training":[136],"on":[137,156],"large-scale":[139],"unlabeled":[140],"pedestrian":[141],"dataset":[142],"LUPerson.":[143],"Finally,":[144],"our":[145],"achieves":[147],"mAP":[149],"87.36%,":[151],"78.26%,":[152],"72.96%,":[153],"57.13%":[155],"Market1501,":[158],"DukeMTMC-reID,":[159],"CUHK03,":[160],"MSMT17":[162],"datasets.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
