{"id":"https://openalex.org/W4224918218","doi":"https://doi.org/10.1109/icassp43922.2022.9747117","title":"Multi-Level Relation Aware Network for Person Re-Identification","display_name":"Multi-Level Relation Aware Network for Person Re-Identification","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224918218","doi":"https://doi.org/10.1109/icassp43922.2022.9747117"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747117","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101516308","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0002-7422-7297"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yang","raw_affiliation_strings":["Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016469515","display_name":"Canlong Zhang","orcid":"https://orcid.org/0000-0003-4375-1405"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Canlong Zhang","raw_affiliation_strings":["Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701695","display_name":"Zhixin Li","orcid":"https://orcid.org/0000-0002-5313-6134"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixin Li","raw_affiliation_strings":["Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Normal University,Guangxi Key Lab of Multi-Source Information Mining Security,Guilin,China,541004","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102180180","display_name":"Yanping Tang","orcid":"https://orcid.org/0000-0003-1683-9356"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanping Tang","raw_affiliation_strings":["Guilin University of Electronic Technology,School of Computer Science and Information Security,Guilin,China,541004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology,School of Computer Science and Information Security,Guilin,China,541004","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2709","last_page":"2713"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991999864578247,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7670219540596008},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7326050996780396},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6792609691619873},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5732396245002747},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.561924159526825},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5592270493507385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399271845817566},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5042997598648071},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4875170886516571},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.48111122846603394},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43777725100517273},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4281652271747589},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35279691219329834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34788039326667786},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20278385281562805},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1314573884010315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11533230543136597}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7670219540596008},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7326050996780396},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6792609691619873},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5732396245002747},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.561924159526825},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5592270493507385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399271845817566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5042997598648071},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4875170886516571},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.48111122846603394},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43777725100517273},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4281652271747589},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35279691219329834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34788039326667786},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20278385281562805},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1314573884010315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11533230543136597},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747117","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2604463754","https://openalex.org/W2889847409","https://openalex.org/W2916798096","https://openalex.org/W2963078173","https://openalex.org/W2963322158","https://openalex.org/W2963557071","https://openalex.org/W2963805953","https://openalex.org/W2963842104","https://openalex.org/W2968039979","https://openalex.org/W2979931389","https://openalex.org/W2979938149","https://openalex.org/W2981393440","https://openalex.org/W3000388098","https://openalex.org/W3013839707","https://openalex.org/W3035186652","https://openalex.org/W3035252826","https://openalex.org/W3035539956","https://openalex.org/W3097537783","https://openalex.org/W3101408564","https://openalex.org/W3110337799","https://openalex.org/W3133975347","https://openalex.org/W6747428963","https://openalex.org/W6760224987"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W3009369890","https://openalex.org/W4312490297","https://openalex.org/W2062212388"],"abstract_inverted_index":{"Person":[0],"attribute":[1,14,40,47,108],"or":[2,13],"pose":[3,12,83],"information":[4],"has":[5],"improved":[6],"person":[7,34],"re-identification":[8],"performance,":[9],"however,":[10],"inaccurate":[11],"module":[15,43,110],"will":[16],"damage":[17],"the":[18,54,68,72,79,94,107,113,122,128],"final":[19],"identification":[20],"performance.":[21],"Based":[22],"on":[23,67,117],"this,":[24],"we":[25,37,60,86],"propose":[26],"a":[27,62,88],"multi-scale":[28],"relation":[29,41,97,109],"aware":[30],"network":[31],"(MSRA)":[32],"for":[33],"re-identification.":[35],"Specifically,":[36],"design":[38],"an":[39,46],"mining":[42],"to":[44,52,77,92,111],"construct":[45,61],"map":[48],"through":[49],"constraint":[50],"loss":[51],"learn":[53],"correlation":[55],"between":[56,82,98],"different":[57,99],"attributes.":[58],"Besides,":[59],"multi-level":[63],"Pose":[64],"Pyramid":[65],"based":[66],"physical":[69],"structure":[70],"of":[71,101,127],"human":[73],"body,":[74],"so":[75],"as":[76],"model":[78],"internal":[80],"relationship":[81],"points.":[84],"Finally,":[85],"designed":[87],"cross-scale":[89],"graph":[90],"convolution":[91],"infer":[93],"cooperative":[95],"structural":[96],"layers":[100],"components":[102],"and":[103,124],"fused":[104],"it":[105],"with":[106],"reinforce":[112],"feature.":[114],"Many":[115],"experiments":[116],"three":[118],"large-scale":[119],"datasets":[120],"verify":[121],"effectiveness":[123],"state-of-the-art":[125],"performance":[126],"proposed":[129],"method.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}