{"id":"https://openalex.org/W2809898047","doi":"https://doi.org/10.1109/tip.2018.2851098","title":"Cross-View Discriminative Feature Learning for Person Re-Identification","display_name":"Cross-View Discriminative Feature Learning for Person Re-Identification","publication_year":2018,"publication_date":"2018-06-27","ids":{"openalex":"https://openalex.org/W2809898047","doi":"https://doi.org/10.1109/tip.2018.2851098","mag":"2809898047","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994678"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2851098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2851098","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pureadmin.qub.ac.uk/ws/files/154016497/cross_view_discriminative_final.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016253801","display_name":"Alessandro Borgia","orcid":"https://orcid.org/0000-0002-2832-837X"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]},{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["GB","MY"],"is_corresponding":true,"raw_author_name":"Alessandro Borgia","raw_affiliation_strings":["ISSS, Heriot-Watt University, Edinburgh, U.K"],"affiliations":[{"raw_affiliation_string":"ISSS, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016123060","display_name":"Hua Yang","orcid":"https://orcid.org/0000-0001-5536-503X"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yang Hua","raw_affiliation_strings":["EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","EEECS/ECIT, Queen's University Belfast, Belfast, U.K"],"affiliations":[{"raw_affiliation_string":"EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]},{"raw_affiliation_string":"EEECS/ECIT, Queen's University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016465304","display_name":"Elyor Kodirov","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096394","display_name":"Queens University","ror":"https://ror.org/00strmv13","country_code":"BD","type":"education","lineage":["https://openalex.org/I4210096394"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Elyor Kodirov","raw_affiliation_strings":["Research Division, Anyvision, Belfast, U.K"],"affiliations":[{"raw_affiliation_string":"Research Division, Anyvision, Belfast, U.K","institution_ids":["https://openalex.org/I4210096394"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102909686","display_name":"Neil M. Robertson","orcid":"https://orcid.org/0000-0003-2461-8799"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Neil M. Robertson","raw_affiliation_strings":["EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","EEECS/ECIT, Queen's University Belfast, Belfast, U.K"],"affiliations":[{"raw_affiliation_string":"EEECS/ECIT, Queen\u2019s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]},{"raw_affiliation_string":"EEECS/ECIT, Queen's University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016253801"],"corresponding_institution_ids":["https://openalex.org/I32062511","https://openalex.org/I4210085930"],"apc_list":null,"apc_paid":null,"fwci":1.9147,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.89931072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"27","issue":"11","first_page":"5338","last_page":"5349"},"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/T11448","display_name":"Face recognition and analysis","score":0.9955999851226807,"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":0.9919000267982483,"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/discriminative-model","display_name":"Discriminative model","score":0.85163414478302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7221808433532715},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6690378189086914},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5913930535316467},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5737947821617126},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5118665099143982},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5021364688873291},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47623923420906067},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4743824303150177},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4701036810874939},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.435963898897171},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42920926213264465},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.42815446853637695},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11286437511444092}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.85163414478302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7221808433532715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6690378189086914},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5913930535316467},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5737947821617126},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5118665099143982},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5021364688873291},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47623923420906067},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4743824303150177},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4701036810874939},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.435963898897171},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42920926213264465},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42815446853637695},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11286437511444092},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2018.2851098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2851098","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:29994678","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994678","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/312f689a-d467-4375-a998-521be3e46e11","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/312f689a-d467-4375-a998-521be3e46e11","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/154016497/cross_view_discriminative_final.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Borgia, A, Hua, Y, Kodirov, E & Robertson, N 2018, 'Cross-view Discriminative Feature Learning for Person Re-Identification', IEEE Trans. on Image Processing, vol. 27, no. 11, pp. 5338 - 5349. https://doi.org/10.1109/TIP.2018.2851098","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/312f689a-d467-4375-a998-521be3e46e11","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/312f689a-d467-4375-a998-521be3e46e11","pdf_url":"https://pureadmin.qub.ac.uk/ws/files/154016497/cross_view_discriminative_final.pdf","source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Borgia, A, Hua, Y, Kodirov, E & Robertson, N 2018, 'Cross-view Discriminative Feature Learning for Person Re-Identification', IEEE Trans. on Image Processing, vol. 27, no. 11, pp. 5338 - 5349. https://doi.org/10.1109/TIP.2018.2851098","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7699999809265137,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311518","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2809898047.pdf","grobid_xml":"https://content.openalex.org/works/W2809898047.grobid-xml"},"referenced_works_count":73,"referenced_works":["https://openalex.org/W170472577","https://openalex.org/W1916279783","https://openalex.org/W1928419358","https://openalex.org/W1971955426","https://openalex.org/W1979260620","https://openalex.org/W1982925187","https://openalex.org/W2014764728","https://openalex.org/W2046835352","https://openalex.org/W2047632871","https://openalex.org/W2084831455","https://openalex.org/W2096733369","https://openalex.org/W2135442311","https://openalex.org/W2138621090","https://openalex.org/W2163605009","https://openalex.org/W2175149598","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2253171278","https://openalex.org/W2258844511","https://openalex.org/W2259687230","https://openalex.org/W2300840837","https://openalex.org/W2337600727","https://openalex.org/W2342611082","https://openalex.org/W2344924411","https://openalex.org/W2361187101","https://openalex.org/W2414767909","https://openalex.org/W2465670578","https://openalex.org/W2467139031","https://openalex.org/W2471048925","https://openalex.org/W2475284720","https://openalex.org/W2478068293","https://openalex.org/W2491664569","https://openalex.org/W2502225121","https://openalex.org/W2519373641","https://openalex.org/W2520774990","https://openalex.org/W2531440880","https://openalex.org/W2553498075","https://openalex.org/W2583528645","https://openalex.org/W2591509103","https://openalex.org/W2591888901","https://openalex.org/W2604211872","https://openalex.org/W2737420735","https://openalex.org/W2738760914","https://openalex.org/W2747359207","https://openalex.org/W2748580836","https://openalex.org/W2752903123","https://openalex.org/W2953350812","https://openalex.org/W2962766801","https://openalex.org/W2962830209","https://openalex.org/W2963161580","https://openalex.org/W2963438548","https://openalex.org/W2963656735","https://openalex.org/W2963775347","https://openalex.org/W2963901085","https://openalex.org/W2964130064","https://openalex.org/W2964289004","https://openalex.org/W2964304299","https://openalex.org/W2964346648","https://openalex.org/W3098057481","https://openalex.org/W3099206234","https://openalex.org/W3099224353","https://openalex.org/W3102668440","https://openalex.org/W6684191040","https://openalex.org/W6693957032","https://openalex.org/W6703042055","https://openalex.org/W6721677572","https://openalex.org/W6722037772","https://openalex.org/W6722869231","https://openalex.org/W6724544503","https://openalex.org/W6730370473","https://openalex.org/W6735013348","https://openalex.org/W6741280430"],"related_works":["https://openalex.org/W3208297503","https://openalex.org/W3119773509","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W2619127353","https://openalex.org/W4309346246","https://openalex.org/W2786094008","https://openalex.org/W3131501806","https://openalex.org/W2799683370","https://openalex.org/W2807745940"],"abstract_inverted_index":{"The":[0,42,81],"viewpoint":[1,150],"variability":[2],"across":[3],"a":[4,10,38,90,122],"network":[5],"of":[6,37,48,78,83,95,102,120,140],"non-overlapping":[7],"cameras":[8],"is":[9,45,87,106],"challenging":[11],"problem":[12],"affecting":[13],"person":[14],"re-identification":[15],"performance.":[16],"In":[17],"this":[18,115],"paper,":[19],"we":[20],"investigate":[21],"how":[22],"to":[23,67,88,144,149],"mitigate":[24],"the":[25,35,51,57,64,75,79,99,103,110,118,129,132,146],"cross-view":[26],"ambiguity":[27],"by":[28,137],"learning":[29,113],"highly":[30],"discriminative":[31],"deep":[32],"features":[33],"under":[34],"supervision":[36,86],"novel":[39],"loss":[40,85],"function.":[41],"proposed":[43],"objective":[44],"made":[46],"up":[47],"two":[49],"terms,":[50],"steering":[52],"meta":[53],"center":[54],"term":[55],"and":[56,71,131,162,170],"enhancing":[58],"centers":[59],"dispersion":[60],"term,":[61],"that":[62],"steer":[63],"training":[65,154],"process":[66],"mining":[68],"effective":[69],"intra-class":[70],"inter-class":[72],"relationships":[73],"in":[74,157],"feature":[76,93],"domain":[77],"identities.":[80],"effect":[82],"our":[84],"generate":[89],"more":[91],"expanded":[92],"space":[94],"compact":[96],"classes":[97],"where":[98],"overall":[100],"level":[101],"inter-identities'":[104],"interference":[105],"reduced.":[107],"Compared":[108],"with":[109],"existing":[111],"metric":[112,133],"techniques,":[114],"approach":[116],"has":[117],"advantage":[119],"achieving":[121],"better":[123],"optimization":[124],"because":[125],"it":[126],"jointly":[127],"learns":[128],"embedding":[130],"contextually.":[134],"Our":[135],"technique,":[136],"dismissing":[138],"side-sources":[139],"performance":[141],"gain,":[142],"proves":[143],"enhance":[145],"CNN":[147],"invariance":[148],"without":[151],"incurring":[152],"increased":[153],"complexity":[155],"(like":[156],"Siamese":[158],"or":[159],"triplet":[160],"networks)":[161],"outperforms":[163],"many":[164],"related":[165],"state-of-the-art":[166],"techniques":[167],"on":[168],"Market-1501":[169],"CUHK03.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
