{"id":"https://openalex.org/W2765995039","doi":"https://doi.org/10.1109/tpami.2017.2764893","title":"Person Re-Identification by Cross-View Multi-Level Dictionary Learning","display_name":"Person Re-Identification by Cross-View Multi-Level Dictionary Learning","publication_year":2017,"publication_date":"2017-10-26","ids":{"openalex":"https://openalex.org/W2765995039","doi":"https://doi.org/10.1109/tpami.2017.2764893","mag":"2765995039","pmid":"https://pubmed.ncbi.nlm.nih.gov/29989963"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2017.2764893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2764893","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100359839","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0003-1205-8632"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sheng Li","raw_affiliation_strings":["Adobe Research, San Jose, CA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028762600","display_name":"Ming Shao","orcid":"https://orcid.org/0000-0002-7686-8784"},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming Shao","raw_affiliation_strings":["Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, MA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, MA","institution_ids":["https://openalex.org/I100633361"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819096","display_name":"Yun Fu","orcid":"https://orcid.org/0000-0002-5098-2853"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Fu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University, Boston, MA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University, Boston, MA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100359839"],"corresponding_institution_ids":["https://openalex.org/I1306409833"],"apc_list":null,"apc_paid":null,"fwci":4.7334,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.97029741,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"40","issue":"12","first_page":"2963","last_page":"2977"},"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":0.9968000054359436,"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":0.9904999732971191,"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/discriminative-model","display_name":"Discriminative model","score":0.8466352820396423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7740339040756226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7265914082527161},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5620187520980835},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5094528794288635},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.48088935017585754},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.4273895025253296},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.42490899562835693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4241853356361389},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4159097671508789},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.41249316930770874},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.3182953894138336}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8466352820396423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7740339040756226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7265914082527161},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5620187520980835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5094528794288635},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.48088935017585754},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.4273895025253296},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.42490899562835693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4241853356361389},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4159097671508789},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.41249316930770874},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.3182953894138336},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2017.2764893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2764893","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:29989963","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29989963","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":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323268","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W41482161","https://openalex.org/W42769906","https://openalex.org/W46454230","https://openalex.org/W98563929","https://openalex.org/W140822990","https://openalex.org/W166429404","https://openalex.org/W198330749","https://openalex.org/W760855798","https://openalex.org/W1142012885","https://openalex.org/W1518138188","https://openalex.org/W1596233070","https://openalex.org/W1605761733","https://openalex.org/W1670132599","https://openalex.org/W1672347394","https://openalex.org/W1709635438","https://openalex.org/W1897123318","https://openalex.org/W1920259731","https://openalex.org/W1927348918","https://openalex.org/W1928419358","https://openalex.org/W1937059634","https://openalex.org/W1941498359","https://openalex.org/W1949591461","https://openalex.org/W1951304353","https://openalex.org/W1962025484","https://openalex.org/W1964590153","https://openalex.org/W1967988963","https://openalex.org/W1979260620","https://openalex.org/W1980222719","https://openalex.org/W1981160672","https://openalex.org/W1982925187","https://openalex.org/W1991452654","https://openalex.org/W1994715454","https://openalex.org/W1999478721","https://openalex.org/W2007588387","https://openalex.org/W2009907187","https://openalex.org/W2018507448","https://openalex.org/W2027805700","https://openalex.org/W2035299679","https://openalex.org/W2046835352","https://openalex.org/W2048110836","https://openalex.org/W2048679005","https://openalex.org/W2062677035","https://openalex.org/W2068042582","https://openalex.org/W2079972027","https://openalex.org/W2082161064","https://openalex.org/W2103024562","https://openalex.org/W2113609219","https://openalex.org/W2115669554","https://openalex.org/W2125889200","https://openalex.org/W2127840337","https://openalex.org/W2130556178","https://openalex.org/W2132175002","https://openalex.org/W2139763424","https://openalex.org/W2140844045","https://openalex.org/W2151065677","https://openalex.org/W2160547390","https://openalex.org/W2163112044","https://openalex.org/W2166371785","https://openalex.org/W2169495281","https://openalex.org/W2186500555","https://openalex.org/W2203864774","https://openalex.org/W2209877316","https://openalex.org/W2220271458","https://openalex.org/W2228002889","https://openalex.org/W2238727627","https://openalex.org/W2272957886","https://openalex.org/W2475284720","https://openalex.org/W2604912015","https://openalex.org/W2963883548","https://openalex.org/W4298190105","https://openalex.org/W6601733005","https://openalex.org/W6601780863","https://openalex.org/W6604005260","https://openalex.org/W6627095619","https://openalex.org/W6636883489","https://openalex.org/W6639781355","https://openalex.org/W6649109542","https://openalex.org/W6675751002","https://openalex.org/W6677018275","https://openalex.org/W6682103744","https://openalex.org/W6682286002","https://openalex.org/W6684213969","https://openalex.org/W6690046996","https://openalex.org/W6736489180"],"related_works":["https://openalex.org/W4287995534","https://openalex.org/W2998168123","https://openalex.org/W1972656095","https://openalex.org/W2157785665","https://openalex.org/W2789775441","https://openalex.org/W2522847406","https://openalex.org/W1982405594","https://openalex.org/W4386307912","https://openalex.org/W2524063692","https://openalex.org/W1914651075"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"plays":[2],"an":[3],"important":[4],"role":[5],"in":[6,41,61,115,191],"many":[7],"safety-critical":[8],"applications.":[9],"Existing":[10],"works":[11],"mainly":[12],"focus":[13],"on":[14,130,220],"extracting":[15],"patch-level":[16],"features":[17,28],"or":[18],"learning":[19,60,81,87,106,135],"distance":[20],"metrics.":[21],"However,":[22],"the":[23,34,47,79,85,113,153,202,213,221,236],"representation":[24,48,139],"power":[25,49],"of":[26,38,50,95,152,160,188],"extracted":[27],"might":[29],"be":[30],"limited,":[31],"due":[32],"to":[33,78,162,178,200,211],"various":[35],"viewing":[36],"conditions":[37],"pedestrian":[39,169],"images":[40],"complex":[42],"real-world":[43],"scenarios.":[44],"To":[45],"improve":[46],"features,":[51],"we":[52,65,120,172],"learn":[53,158],"discriminative":[54,175,189],"and":[55,145,156,165,180,193,228],"robust":[56,164],"representations":[57,167],"via":[58],"dictionary":[59,86,117,134],"this":[62],"paper.":[63],"First,":[64],"propose":[66,121,181],"a":[67,75,93,104,122,174,182,206],"Cross-view":[68,123],"Dictionary":[69,125],"Learning":[70,126],"(CDL)":[71],"model,":[72],"which":[73,108,185],"is":[74,109,209],"general":[76],"solution":[77],"multi-view":[80],"problem.":[82],"Inspired":[83],"by":[84],"based":[88,129],"domain":[89],"adaptation,":[90],"CDL":[91,102],"learns":[92,186],"pair":[94],"dictionaries":[96,161,190],"from":[97],"two":[98],"views.":[99],"In":[100],"particular,":[101],"adopts":[103],"projective":[105],"strategy,":[107],"more":[110],"efficient":[111,197],"than":[112],"optimization":[114,198],"traditional":[116],"learning.":[118],"Second,":[119],"Multi-level":[124],"(CMDL)":[127],"approach":[128,184,234],"CDL.":[131],"CMDL":[132],"contains":[133],"models":[136,149],"at":[137],"different":[138],"levels,":[140],"including":[141],"image-level,":[142],"horizontal":[143],"part-level,":[144],"patch-level.":[146],"The":[147],"proposed":[148,203],"take":[150],"advantages":[151],"view-consistency":[154],"information,":[155],"adaptively":[157],"pairs":[159,187],"generate":[163,212],"compact":[166],"for":[168,216],"images.":[170,218],"Third,":[171],"incorporate":[173],"regularization":[176],"term":[177],"CMDL,":[179],"CMDL-Dis":[183],"image-level":[192],"part-level.":[194],"We":[195],"devise":[196],"algorithms":[199],"solve":[201],"models.":[204],"Finally,":[205],"fusion":[207],"strategy":[208],"utilized":[210],"similarity":[214],"scores":[215],"test":[217],"Experiments":[219],"public":[222],"VIPeR,":[223],"CUHK":[224],"Campus,":[225],"iLIDS,":[226],"GRID":[227],"PRID450S":[229],"datasets":[230],"show":[231],"that":[232],"our":[233],"achieves":[235],"state-of-the-art":[237],"performance.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":8}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}