{"id":"https://openalex.org/W4320712925","doi":"https://doi.org/10.1109/access.2023.3243553","title":"A Double Stream Person Re-Identification Method Based on Attention Mechanism and Multi-Scale Feature Fusion","display_name":"A Double Stream Person Re-Identification Method Based on Attention Mechanism and Multi-Scale Feature Fusion","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4320712925","doi":"https://doi.org/10.1109/access.2023.3243553"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3243553","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3243553","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10043774.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10043774.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100743784","display_name":"Xiao Ma","orcid":"https://orcid.org/0000-0001-5831-0368"},"institutions":[{"id":"https://openalex.org/I168337820","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52","country_code":"CN","type":"education","lineage":["https://openalex.org/I168337820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Ma","raw_affiliation_strings":["School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-5831-0368","affiliations":[{"raw_affiliation_string":"School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China","institution_ids":["https://openalex.org/I168337820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112845768","display_name":"Wenqi Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I168337820","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52","country_code":"CN","type":"education","lineage":["https://openalex.org/I168337820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqi Lv","raw_affiliation_strings":["School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China","institution_ids":["https://openalex.org/I168337820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103058407","display_name":"Meng Zhao","orcid":"https://orcid.org/0000-0002-1357-7808"},"institutions":[{"id":"https://openalex.org/I168337820","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52","country_code":"CN","type":"education","lineage":["https://openalex.org/I168337820"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Zhao","raw_affiliation_strings":["School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-1357-7808","affiliations":[{"raw_affiliation_string":"School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China","institution_ids":["https://openalex.org/I168337820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I168337820"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4891,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.84128565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"14612","last_page":"14620"},"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":0.9984999895095825,"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":0.9962999820709229,"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":0.8415980339050293},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7395622134208679},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6823074817657471},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5828949809074402},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5247854590415955},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5215761065483093},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49566566944122314},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4265154302120209},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4118998050689697},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.19363322854042053}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8415980339050293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7395622134208679},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6823074817657471},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5828949809074402},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5247854590415955},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5215761065483093},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49566566944122314},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4265154302120209},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4118998050689697},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.19363322854042053},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3243553","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3243553","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10043774.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7d0c5d1b17e140858cf5bf006254cda5","is_oa":true,"landing_page_url":"https://doaj.org/article/7d0c5d1b17e140858cf5bf006254cda5","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":"IEEE Access, Vol 11, Pp 14612-14620 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3243553","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3243553","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10043774.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5458774672","display_name":null,"funder_award_id":"ckrc2019032","funder_id":"https://openalex.org/F4320328771","funder_display_name":"Chongqing University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320328771","display_name":"Chongqing University of Science and Technology","ror":"https://ror.org/03n3v6d52"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4320712925.pdf","grobid_xml":"https://content.openalex.org/works/W4320712925.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2131255818","https://openalex.org/W2157643754","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2432402544","https://openalex.org/W2585635281","https://openalex.org/W2598634450","https://openalex.org/W2604463754","https://openalex.org/W2606377603","https://openalex.org/W2737725206","https://openalex.org/W2752782242","https://openalex.org/W2773003563","https://openalex.org/W2798874329","https://openalex.org/W2810967842","https://openalex.org/W2887695188","https://openalex.org/W2947319827","https://openalex.org/W2962706983","https://openalex.org/W2962926870","https://openalex.org/W2963047834","https://openalex.org/W2963049565","https://openalex.org/W2963842104","https://openalex.org/W2963852441","https://openalex.org/W2963899050","https://openalex.org/W2963901085","https://openalex.org/W2963910742","https://openalex.org/W2964130064","https://openalex.org/W2964304299","https://openalex.org/W2979931389","https://openalex.org/W2980073905","https://openalex.org/W2981420411","https://openalex.org/W2982119297","https://openalex.org/W2992183111","https://openalex.org/W2993325947","https://openalex.org/W3034552520","https://openalex.org/W3034580371","https://openalex.org/W3035186652","https://openalex.org/W3035539956","https://openalex.org/W3047312295","https://openalex.org/W3098711604","https://openalex.org/W3100555577","https://openalex.org/W3101408564","https://openalex.org/W3105159632","https://openalex.org/W3111255625","https://openalex.org/W3124561108","https://openalex.org/W3175823695","https://openalex.org/W3191741720","https://openalex.org/W4205720260","https://openalex.org/W6768952390"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W2965546495","https://openalex.org/W3204901196"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"is":[2,124,224],"the":[3,39,55,59,64,74,78,87,93,106,127,133,139,143,149,154,161,165,174,177,182,198,228,234,245,250,254],"key":[4],"technology":[5],"for":[6,193],"designing":[7],"a":[8,17,21,28,48,98,212],"intelligent":[9],"video":[10],"surveillance":[11,65],"system":[12],"to":[13,36,84,130,226],"retrieve":[14],"and":[15,81,160,181,189,197,202,221,242,260],"recongise":[16],"specific":[18],"person":[19,41],"in":[20,30,58],"series":[22],"of":[23,42,76,89,109,138,153,186,206],"videos.":[24],"It":[25],"mainly":[26],"plays":[27],"role":[29],"multiple":[31],"non-overlapping":[32],"camera":[33,49,66],"monitoring":[34],"environments":[35],"determine":[37],"whether":[38],"target":[40],"interest":[43],"that":[44,249],"has":[45],"appeared":[46],"under":[47,52,112],"appears":[50],"again":[51],"others.":[53],"However,":[54],"image":[56,150],"data,":[57],"real":[60],"scene,":[61],"taken":[62],"by":[63,115,164,253],"may":[67],"be":[68,158,171],"occluded":[69],"or":[70],"blurred,":[71],"which":[72,104,217],"increased":[73],"difficulty":[75],"identifying":[77],"pedestrian":[79,110,118],"posturn":[80],"then":[82],"lead":[83],"dramatically":[85],"decrease":[86],"accuracy":[88],"recognition.":[90],"To":[91],"solve":[92],"above":[94],"problems,":[95],"we":[96],"propose":[97],"dualbranch":[99],"multi-scale":[100],"feature":[101,121,135],"fusion":[102],"network,":[103],"improves":[105],"expression":[107],"ability":[108,137],"features":[111,152,251],"partial":[113],"occlusion":[114],"learning":[116,136],"discriminative":[117,259],"features.":[119],"The":[120],"erasure":[122],"mechanism":[123],"introduced":[125],"into":[126,147],"branch":[128],"network":[129,229],"effectively":[131],"enhance":[132],"fine-grained":[134],"network.":[140],"By":[141,231],"embedding":[142],"lightweight":[144],"attention":[145],"module":[146],"Resnet-50,":[148],"sequence":[151],"channel":[155],"dimension":[156],"will":[157,170],"extracted,":[159],"interference":[162],"caused":[163],"cluttered":[166],"back":[167],"ground":[168],"information":[169],"suppressed.":[172],"In":[173],"training":[175],"phase,":[176],"average":[178],"pooling":[179,184,200],"layer":[180,185],"maximum":[183],"different":[187,194,207],"kernels":[188,208],"strides":[190],"are":[191,209,257],"utilized":[192],"residual":[195],"stages,":[196],"mixed":[199,203],"strategy":[201],"loss":[204,215,220,223],"function":[205,216],"designed.":[210],"Finally,":[211],"novel":[213],"hybrid":[214],"combines":[218],"triplet":[219],"ID":[222],"presented":[225],"train":[227],"model.":[230],"comparison":[232],"with":[233,261],"existing":[235],"representative":[236],"methods":[237],"on":[238],"Market1501,":[239],"DukeMTMC":[240],"reID":[241],"MTMS17":[243],"datasets,":[244],"experimental":[246],"results":[247],"show":[248],"extracted":[252],"proposed":[255],"method":[256],"more":[258],"high":[262],"recognition":[263],"accuracy.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}