{"id":"https://openalex.org/W3157541723","doi":"https://doi.org/10.1109/icpr48806.2021.9412098","title":"Local Attention and Global Representation Collaborating for Fine-grained Classification","display_name":"Local Attention and Global Representation Collaborating for Fine-grained Classification","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3157541723","doi":"https://doi.org/10.1109/icpr48806.2021.9412098","mag":"3157541723"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5100420147","display_name":"He Zhang","orcid":"https://orcid.org/0000-0003-2304-9387"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Zhang","raw_affiliation_strings":["Beijing IrisKing Co., Ltd","Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing IrisKing Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008253314","display_name":"Yunming Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunming Bai","raw_affiliation_strings":["Forenisc Science Center of Guangdong Provincial Public Security Bureau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Forenisc Science Center of Guangdong Provincial Public Security Bureau","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108035744","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0003-0601-3905"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Beijing IrisKing Co., Ltd","Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing IrisKing Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375073","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-9031-6433"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["Beijing IrisKing Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing IrisKing Co., Ltd","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101678769","display_name":"Xingguang Li","orcid":"https://orcid.org/0000-0002-5964-8843"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingguang Li","raw_affiliation_strings":["Beijing IrisKing Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing IrisKing Co., Ltd","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101869968","display_name":"Zhaofeng He","orcid":"https://orcid.org/0000-0002-0110-0156"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaofeng He","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7252,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67642187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"10658","last_page":"10665"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9567999839782715,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10751","display_name":"Forensic and Genetic Research","score":0.9315999746322632,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8481436967849731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7682192325592041},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.7519385814666748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6707706451416016},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.6307539939880371},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5161398649215698},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4637129604816437},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4288439154624939},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3315693736076355},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.10867297649383545}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8481436967849731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682192325592041},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.7519385814666748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707706451416016},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.6307539939880371},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5161398649215698},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4637129604816437},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4288439154624939},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3315693736076355},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.10867297649383545},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1516591826","https://openalex.org/W1686810756","https://openalex.org/W1797268635","https://openalex.org/W1899185266","https://openalex.org/W1992358283","https://openalex.org/W2024178148","https://openalex.org/W2051068139","https://openalex.org/W2068779413","https://openalex.org/W2104657103","https://openalex.org/W2122759487","https://openalex.org/W2123625324","https://openalex.org/W2151532442","https://openalex.org/W2295107390","https://openalex.org/W2396418662","https://openalex.org/W2403790759","https://openalex.org/W2479109623","https://openalex.org/W2613902731","https://openalex.org/W2737725206","https://openalex.org/W2764076527","https://openalex.org/W2765268259","https://openalex.org/W2766867864","https://openalex.org/W2798365843","https://openalex.org/W2884974918","https://openalex.org/W2896632102","https://openalex.org/W2952047972","https://openalex.org/W2953384591","https://openalex.org/W2963070273","https://openalex.org/W2963725249","https://openalex.org/W2963733622","https://openalex.org/W2963749936","https://openalex.org/W4285719527","https://openalex.org/W6637373629","https://openalex.org/W6678326819","https://openalex.org/W6713134421","https://openalex.org/W6737550521"],"related_works":["https://openalex.org/W8021621","https://openalex.org/W1373283","https://openalex.org/W10234003","https://openalex.org/W2023756","https://openalex.org/W9516802","https://openalex.org/W13726599","https://openalex.org/W181698","https://openalex.org/W4884292","https://openalex.org/W7592732","https://openalex.org/W4429616"],"abstract_inverted_index":{"The":[0,76,118,151],"cosmetic":[1,22,37,73],"contact":[2,38,74],"lenses":[3,23,39],"over":[4],"an":[5],"iris":[6,10,18,28,55,148,157],"may":[7],"change":[8],"original":[9],"textural":[11],"pattern":[12],"which":[13,105],"is":[14,98,161],"the":[15,21,36,47,72,91,95,107,114,165],"foundation":[16],"for":[17,109,164],"recognition,":[19],"making":[20],"a":[24,62,79,85,144],"possible":[25],"and":[26,51,84,112,128,143,160],"easy-to-use":[27],"presentation":[29],"attack":[30],"means.":[31],"For":[32],"practical":[33],"application":[34],"scenes,":[35],"detection":[40,111,158],"still":[41],"facing":[42],"unsolved":[43],"problems,":[44],"due":[45],"to":[46,70,100],"low":[48],"image":[49,149,167],"quality":[50],"difficulty":[52],"in":[53],"accurately":[54],"localization.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"propose":[61],"novel":[63],"framework":[64],"called":[65],"Weighted":[66],"Region":[67,88],"Network":[68,83,120],"(WRN)":[69],"detect":[71],"lenses.":[75],"WRN":[77],"includes":[78],"local":[80],"attention":[81,93],"Weight":[82,119],"global":[86],"classification":[87,168],"Network.":[89],"With":[90],"inherent":[92],"mechanism,":[94],"proposed":[96,152],"network":[97],"able":[99],"find":[101],"more":[102],"discriminative":[103,133],"regions,":[104],"reduces":[106],"requirement":[108],"target":[110],"improves":[113],"ability":[115],"of":[116],"classification.":[117],"can":[121],"be":[122],"trained":[123],"by":[124],"using":[125],"Rank":[126],"loss":[127,130],"MSE":[129],"without":[131],"manual":[132],"region":[134],"annotations.":[135],"Experiments":[136],"are":[137],"conducted":[138],"on":[139],"several":[140],"public":[141],"databases":[142],"new":[145],"collected":[146],"low-quality":[147],"database.":[150],"method":[153],"outperforms":[154],"state-of-the-art":[155],"fake":[156],"algorithms,":[159],"also":[162],"effective":[163],"fine-grained":[166],"task.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}