{"id":"https://openalex.org/W2793568338","doi":"https://doi.org/10.1109/itsc.2017.8317817","title":"VRID-1: A basic vehicle re-identification dataset for similar vehicles","display_name":"VRID-1: A basic vehicle re-identification dataset for similar vehicles","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2793568338","doi":"https://doi.org/10.1109/itsc.2017.8317817","mag":"2793568338"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2017.8317817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","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/A5077419230","display_name":"Xiying Li","orcid":"https://orcid.org/0000-0002-4753-8022"},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiying Li","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210113138"]},{"raw_affiliation_string":"Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I1302611135"]},{"raw_affiliation_string":"Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100554721","display_name":"Minxian Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minxian Yuan","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210113138"]},{"raw_affiliation_string":"Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I1302611135"]},{"raw_affiliation_string":"Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072615359","display_name":"Qianyin Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianyin Jiang","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210113138"]},{"raw_affiliation_string":"Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I1302611135"]},{"raw_affiliation_string":"Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752569","display_name":"Guoming Li","orcid":"https://orcid.org/0000-0001-7624-8051"},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoming Li","raw_affiliation_strings":["Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Laboratory of Intelligent Transportation Systems, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210113138"]},{"raw_affiliation_string":"Ministry of Public Security, Key Laboratory of Video and Image Intelligent Analysis and Application Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I1302611135"]},{"raw_affiliation_string":"Research Center of Intelligent Transportation Systems, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"2017","issue":null,"first_page":"1","last_page":"8"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/identification","display_name":"Identification (biology)","score":0.8554394245147705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7472242116928101},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7189205884933472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6373482942581177},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5616865158081055},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4921933710575104},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45623230934143066},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43218931555747986},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38772860169410706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3609326481819153},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08547070622444153}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.8554394245147705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472242116928101},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7189205884933472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6373482942581177},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5616865158081055},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4921933710575104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45623230934143066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43218931555747986},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38772860169410706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3609326481819153},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08547070622444153},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2017.8317817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"mag:3139098725","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201802212998931244","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W977823703","https://openalex.org/W1686810756","https://openalex.org/W1927348918","https://openalex.org/W1928419358","https://openalex.org/W1949591461","https://openalex.org/W1958236864","https://openalex.org/W1971955426","https://openalex.org/W2016698498","https://openalex.org/W2027922120","https://openalex.org/W2079972027","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2116088207","https://openalex.org/W2139212933","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2203864774","https://openalex.org/W2342611082","https://openalex.org/W2495961871","https://openalex.org/W2512434173","https://openalex.org/W2963542991","https://openalex.org/W6620707391","https://openalex.org/W6629368666","https://openalex.org/W6637373629","https://openalex.org/W6640310490","https://openalex.org/W6684191040","https://openalex.org/W6687483927"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Vehicle":[0],"re-identification":[1,50,89,170,199],"is":[2,34,47,224],"a":[3,7,70,83,172,188],"process":[4],"of":[5,17,24,27,30,41,60,63,103,107,126,155,161,168,182,219],"recognising":[6],"vehicle":[8,49,78,88,112,116,169,183,198,229],"at":[9,133],"different":[10,134],"locations.":[11,135],"It":[12],"has":[13],"attracted":[14],"increasing":[15],"amounts":[16],"attention":[18],"due":[19],"to":[20,68,179,192],"the":[21,31,39,54,58,64,87,108,166,180,207,220],"rapidly-increasing":[22],"number":[23],"vehicles.":[25],"Identification":[26],"two":[28],"vehicles":[29,62,106,151,218],"same":[32,65,221],"model":[33],"even":[35],"more":[36],"difficult":[37],"than":[38],"identification":[40],"identical":[42],"twin":[43],"humans.":[44],"Further-more,":[45],"there":[46,118,128,148],"no":[48],"dataset":[51,85,209],"that":[52,211],"considers":[53],"interference":[55,216],"caused":[56],"by":[57,142],"presence":[59],"other":[61],"model.":[66],"Therefore,":[67],"provide":[69],"fair":[71],"comparison":[72],"and":[73,123,146,153,223,226],"facilitate":[74],"future":[75],"research":[76],"into":[77],"re-identification,":[79],"this":[80,185],"paper":[81,186],"constructs":[82],"new":[84],"called":[86],"dataset-1":[90],"(":[91],"<sup":[92],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[93],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[94],"VRID-1).":[95],"VRID-1":[96,139,208],"contains":[97],"10,000":[98],"images":[99,131,137,160],"captured":[100,132,141],"in":[101,138,171],"daytime":[102],"1,000":[104],"individual":[105,121],"ten":[109,130],"most":[110],"common":[111],"models.":[113],"For":[114],"each":[115,125],"model,":[117,222],"are":[119,129,149],"100":[120],"vehicles,":[122],"for":[124,165,197,228],"these,":[127],"The":[136],"were":[140],"326":[143],"surveillance":[144,174],"cameras,":[145],"thus":[147],"various":[150],"poses":[152],"levels":[154],"illumination.":[156],"Yet,":[157],"it":[158,212],"provides":[159],"good":[162],"enough":[163],"quality":[164],"evaluation":[167],"practical":[173,227],"environment.":[175],"In":[176],"addition,":[177],"according":[178],"characteristics":[181],"morphology,":[184],"proposes":[187],"deep":[189],"learning-based":[190],"method":[191],"extract":[193],"multi-dimensional":[194],"robust":[195],"features":[196],"using":[200],"convolutional":[201],"neural":[202],"networks.":[203],"Experimental":[204],"results":[205],"on":[206],"demonstrate":[210],"can":[213],"deal":[214],"with":[215],"from":[217],"effective":[225],"re-identification.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}