{"id":"https://openalex.org/W4385453401","doi":"https://doi.org/10.1109/tnnls.2023.3297134","title":"Boosting Zero-Shot Learning via Contrastive Optimization of Attribute Representations","display_name":"Boosting Zero-Shot Learning via Contrastive Optimization of Attribute Representations","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385453401","doi":"https://doi.org/10.1109/tnnls.2023.3297134","pmid":"https://pubmed.ncbi.nlm.nih.gov/37527321"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3297134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3297134","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5102776981","display_name":"Yu Du","orcid":"https://orcid.org/0009-0004-3663-3130"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Du","raw_affiliation_strings":["Department of Precision Instrument, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-3663-3130","affiliations":[{"raw_affiliation_string":"Department of Precision Instrument, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101675323","display_name":"Miaojing Shi","orcid":"https://orcid.org/0000-0002-4933-0073"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miaojing Shi","raw_affiliation_strings":["College of Electronic and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4933-0073","affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090973869","display_name":"Fangyun Wei","orcid":"https://orcid.org/0000-0001-8784-4916"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangyun Wei","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8784-4916","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018970859","display_name":"Guoqi Li","orcid":"https://orcid.org/0000-0002-8994-431X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqi Li","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8994-431X","affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9369,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.92698973,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"16706","last_page":"16719"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9214000105857849,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9107000231742859,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/embedding","display_name":"Embedding","score":0.7841917276382446},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.741997480392456},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6907074451446533},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5956719517707825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5833257436752319},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4902651607990265},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4731622338294983},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.47177910804748535},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4356609582901001},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4037289321422577},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32039982080459595},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13578549027442932}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7841917276382446},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741997480392456},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6907074451446533},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5956719517707825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5833257436752319},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4902651607990265},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4731622338294983},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.47177910804748535},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4356609582901001},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4037289321422577},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32039982080459595},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13578549027442932},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3297134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3297134","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37527321","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37527321","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G124397460","display_name":null,"funder_award_id":"62236009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7861851748","display_name":"\u901a\u7528\u7c7b\u8111\u8ba1\u7b97\u67b6\u6784\u6a21\u578b\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61836004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1492420801","https://openalex.org/W1686810756","https://openalex.org/W2032699694","https://openalex.org/W2104657103","https://openalex.org/W2194775991","https://openalex.org/W2552383788","https://openalex.org/W2565639579","https://openalex.org/W2596142952","https://openalex.org/W2604415738","https://openalex.org/W2724492314","https://openalex.org/W2769439543","https://openalex.org/W2788455775","https://openalex.org/W2883124384","https://openalex.org/W2896457183","https://openalex.org/W2910453440","https://openalex.org/W2911322662","https://openalex.org/W2963499153","https://openalex.org/W2963545832","https://openalex.org/W2963960318","https://openalex.org/W2964105864","https://openalex.org/W2979571231","https://openalex.org/W2982407353","https://openalex.org/W2991221721","https://openalex.org/W2991813857","https://openalex.org/W2996834220","https://openalex.org/W3034359780","https://openalex.org/W3034379915","https://openalex.org/W3034730995","https://openalex.org/W3035524453","https://openalex.org/W3035655772","https://openalex.org/W3043752659","https://openalex.org/W3089741414","https://openalex.org/W3096655658","https://openalex.org/W3096741441","https://openalex.org/W3098690786","https://openalex.org/W3099554308","https://openalex.org/W3138357030","https://openalex.org/W3143107425","https://openalex.org/W3153121266","https://openalex.org/W3155179280","https://openalex.org/W3171007011","https://openalex.org/W3171926364","https://openalex.org/W3176716813","https://openalex.org/W3182605419","https://openalex.org/W3191452491","https://openalex.org/W3203055845","https://openalex.org/W4229482837","https://openalex.org/W4239025696","https://openalex.org/W4287472508","https://openalex.org/W4312762894","https://openalex.org/W4312791158","https://openalex.org/W4312900176","https://openalex.org/W4385245566","https://openalex.org/W6600609147","https://openalex.org/W6621740533","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6735236233","https://openalex.org/W6746056662","https://openalex.org/W6755207826","https://openalex.org/W6758306004","https://openalex.org/W6776700526","https://openalex.org/W6778883912","https://openalex.org/W6781630272","https://openalex.org/W6784522328","https://openalex.org/W6785800702","https://openalex.org/W6788439910","https://openalex.org/W6791312233","https://openalex.org/W6800053997","https://openalex.org/W6802136708"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W4239293476","https://openalex.org/W1566995892"],"abstract_inverted_index":{"Zero-shot":[0],"learning":[1,98],"(ZSL)":[2],"aims":[3],"to":[4,20,78,93,131,145,161],"recognize":[5],"classes":[6],"that":[7,190],"do":[8],"not":[9,83],"have":[10],"samples":[11],"in":[12,149],"the":[13,69,79,113,150,194,197],"training":[14],"set.":[15],"One":[16],"representative":[17],"solution":[18],"is":[19,129,143],"directly":[21],"learn":[22],"an":[23],"embedding":[24,151],"function":[25],"associating":[26],"visual":[27],"features":[28,52,60,73,109,148],"with":[29,107,181],"corresponding":[30],"class":[31],"semantics":[32],"for":[33,72,120],"recognizing":[34],"new":[35,91,124],"classes.":[36],"Many":[37],"methods":[38],"extend":[39],"upon":[40],"this":[41,86],"solution,":[42],"and":[43,103,159,165,179],"recent":[44],"ones":[45],"are":[46,61,82,118],"especially":[47],"keen":[48],"on":[49,168,186],"extracting":[50],"rich":[51],"from":[53,135],"images,":[54],"e.g.,":[55],"attribute":[56,59,81,99,121,133,136,176],"features.":[57],"These":[58],"normally":[62],"extracted":[63],"within":[64,110],"each":[65],"individual":[66],"image;":[67],"however,":[68],"common":[70],"traits":[71],"across":[74],"images":[75,102],"yet":[76],"belonging":[77],"same":[80],"emphasized.":[84],"In":[85],"article,":[87],"we":[88],"propose":[89],"a":[90,123,138,200],"framework":[92,164],"boost":[94],"ZSL":[95],"by":[96,199],"explicitly":[97],"prototypes":[100,134],"beyond":[101],"contrastively":[104],"optimizing":[105],"them":[106],"attribute-level":[108,147],"images.":[111],"Besides":[112],"novel":[114],"architecture,":[115],"two":[116,155],"elements":[117],"highlighted":[119],"representations:":[122],"prototype":[125],"generation":[126],"module":[127],"(PM)":[128],"designed":[130],"generate":[132],"semantics;":[137],"hard-example-based":[139],"contrastive":[140],"optimization":[141],"scheme":[142],"introduced":[144],"reinforce":[146],"space.":[152],"We":[153],"explore":[154],"alternative":[156],"backbones,":[157],"CNN-based":[158],"transformer-based,":[160],"build":[162],"our":[163,191],"conduct":[166],"experiments":[167],"three":[169],"standard":[170],"benchmarks,":[171],"Caltech-UCSD":[172],"Birds-200-2011":[173],"(CUB),":[174],"SUN":[175],"database":[177],"(SUN),":[178],"animals":[180],"attributes":[182],"2":[183],"(AwA2).":[184],"Results":[185],"these":[187],"benchmarks":[188],"demonstrate":[189],"method":[192],"improves":[193],"state":[195],"of":[196],"art":[198],"considerable":[201],"margin.":[202],"Our":[203],"codes":[204],"will":[205],"be":[206],"available":[207],"at":[208],"https://github.com/dyabel/CoAR-ZSL.git.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2023-08-02T00:00:00"}
