{"id":"https://openalex.org/W3016056282","doi":"https://doi.org/10.1109/icassp40776.2020.9053328","title":"Multi-Scale Deep Feature Fusion for Vehicle Re-Identification","display_name":"Multi-Scale Deep Feature Fusion for Vehicle Re-Identification","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3016056282","doi":"https://doi.org/10.1109/icassp40776.2020.9053328","mag":"3016056282"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5101523911","display_name":"Yiting Cheng","orcid":"https://orcid.org/0000-0002-8331-9740"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiting Cheng","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001130529","display_name":"Chuanfa Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanfa Zhang","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010756868","display_name":"Kangzheng Gu","orcid":"https://orcid.org/0009-0004-4909-3022"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangzheng Gu","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009450745","display_name":"Lizhe Qi","orcid":"https://orcid.org/0000-0002-4348-1559"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhe Qi","raw_affiliation_strings":["Academy for Engineering & Technology, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy for Engineering & Technology, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067539236","display_name":"Zhongxue Gan","orcid":"https://orcid.org/0000-0003-3873-5187"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxue Gan","raw_affiliation_strings":["Academy for Engineering & Technology, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy for Engineering & Technology, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100669255","display_name":"Wenqiang Zhang","orcid":"https://orcid.org/0000-0002-3339-8751"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Zhang","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1928","last_page":"1932"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7382898330688477},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7283386588096619},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6990381479263306},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6772372722625732},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.65207439661026},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5986621379852295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5613155364990234},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5335498452186584},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.449938029050827},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41766297817230225},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4144562780857086},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09279105067253113}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7382898330688477},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7283386588096619},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6990381479263306},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6772372722625732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65207439661026},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5986621379852295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5613155364990234},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5335498452186584},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.449938029050827},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41766297817230225},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4144562780857086},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09279105067253113},{"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/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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/W1949591461","https://openalex.org/W2194775991","https://openalex.org/W2470322391","https://openalex.org/W2519904008","https://openalex.org/W2752782242","https://openalex.org/W2776879428","https://openalex.org/W2779954854","https://openalex.org/W2788212895","https://openalex.org/W2798794112","https://openalex.org/W2799251491","https://openalex.org/W2807859372","https://openalex.org/W2885476150","https://openalex.org/W2938503583","https://openalex.org/W2955854238","https://openalex.org/W2962706983","https://openalex.org/W2963365374","https://openalex.org/W2963420686","https://openalex.org/W2963749936","https://openalex.org/W2963977416","https://openalex.org/W2984145721","https://openalex.org/W6743731764"],"related_works":["https://openalex.org/W2001271057","https://openalex.org/W2522537526","https://openalex.org/W2998228095","https://openalex.org/W2791535170","https://openalex.org/W4308659218","https://openalex.org/W2468641972","https://openalex.org/W1586536980","https://openalex.org/W3172041118","https://openalex.org/W3042635963","https://openalex.org/W4200210037"],"abstract_inverted_index":{"Vehicle":[0],"re-identification":[1],"(re-id)":[2],"is":[3,102,115],"challenging":[4,143],"due":[5],"to":[6,42,91,104,119],"the":[7,55,93,121],"small":[8],"inter-class":[9],"distance.":[10],"The":[11],"differences":[12],"between":[13],"similar":[14],"vehicles":[15],"can":[16],"be":[17],"extremely":[18],"subtle":[19],"and":[20,26,46,112,145,152],"only":[21],"captured":[22],"at":[23],"particular":[24],"scales":[25],"semantic":[27],"levels.":[28,130],"In":[29],"this":[30],"paper,":[31],"we":[32],"propose":[33],"a":[34,132],"novel":[35],"Multi-Scale":[36,66,99],"Deep":[37],"Feature":[38],"Fusion":[39,67,81],"Network":[40],"(MSDeep)":[41],"conduct":[43],"both":[44],"multi-scale":[45,74],"multi-level":[47],"features":[48,87],"for":[49,124],"precise":[50],"vehicle":[51],"re-id.":[52],"Based":[53],"on":[54,142],"backbone":[56],"deep":[57],"CNN,":[58],"MS-Deep":[59],"mainly":[60],"consists":[61],"of":[62,73,88,109,128,150],"two":[63],"modules:":[64],"1)":[65],"(MSF)":[68],"Block":[69,83],"which":[70,84],"encapsulates":[71],"combination":[72],"streams":[75],"as":[76],"MSF":[77,86,126],"feature;":[78],"2)":[79],"Multi-Level":[80],"(MLF)":[82],"fuses":[85],"multiple":[89],"levels":[90],"build":[92],"final":[94],"descriptor.":[95],"Importantly,":[96],"in":[97,117,148],"MSF,":[98],"Attention":[100],"(MSA)":[101],"introduced":[103],"dynamically":[105],"emphasize":[106],"important":[107],"channels":[108],"each":[110,125],"scale,":[111],"Level-Wise":[113],"Attention(LWA)":[114],"utilized":[116],"MLF":[118],"determine":[120],"different":[122,129],"weightings":[123],"feature":[127],"As":[131],"result,":[133],"experiments":[134],"show":[135],"that":[136],"our":[137],"MSDeep":[138],"outperforms":[139],"state-of-the-art":[140],"algorithms":[141],"VeRi":[144],"VehicleID":[146],"benchmarks":[147],"terms":[149],"abundant":[151],"hierarchical":[153],"hyper-descriptors.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}