{"id":"https://openalex.org/W3009789619","doi":"https://doi.org/10.1109/wacv45572.2020.9093282","title":"Model-Agnostic Metric for Zero-Shot Learning","display_name":"Model-Agnostic Metric for Zero-Shot Learning","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3009789619","doi":"https://doi.org/10.1109/wacv45572.2020.9093282","mag":"3009789619"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"article","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/A5100766009","display_name":"Jiayi Shen","orcid":"https://orcid.org/0000-0002-6348-2559"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayi Shen","raw_affiliation_strings":["Beihang University,School of Electronic and Information Engineering,Beijing,China","School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronic and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100645300","display_name":"Haochen Wang","orcid":"https://orcid.org/0000-0003-3178-6125"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haochen Wang","raw_affiliation_strings":["Beihang University,School of Electronic and Information Engineering,Beijing,China","School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronic and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010938580","display_name":"Anran Zhang","orcid":"https://orcid.org/0000-0003-2413-5439"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anran Zhang","raw_affiliation_strings":["Beihang University,School of Electronic and Information Engineering,Beijing,China","School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronic and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101992408","display_name":"Qiang Qiu","orcid":"https://orcid.org/0000-0003-2610-3502"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Qiu","raw_affiliation_strings":["Duke University,Durham,NC,USA","Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Duke University,Durham,NC,USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026486701","display_name":"Xiantong Zhen","orcid":"https://orcid.org/0000-0001-5213-0462"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Xiantong Zhen","raw_affiliation_strings":["Inception Institute of Artificial Intelligence,Abu Dhabi,UAE","Inception Institute of Artificial Intelligence, Abu Dhabi, UAE"],"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence,Abu Dhabi,UAE","institution_ids":["https://openalex.org/I4210116052"]},{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, UAE","institution_ids":["https://openalex.org/I4210116052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038809760","display_name":"Xianbin Cao","orcid":"https://orcid.org/0000-0002-5042-7884"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianbin Cao","raw_affiliation_strings":["Beihang University,School of Electronic and Information Engineering,Beijing,China","School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronic and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100766009"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.6628,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7488589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"775","last_page":"784"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9625999927520752,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9465000033378601,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7610001564025879},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6611286997795105},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6480824947357178},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.6179494857788086},{"id":"https://openalex.org/keywords/trigonometric-functions","display_name":"Trigonometric functions","score":0.6103761196136475},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6101497411727905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47975099086761475},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4696238338947296},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4308955669403076},{"id":"https://openalex.org/keywords/euclidean-space","display_name":"Euclidean space","score":0.4225386381149292},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42120349407196045},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41461181640625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34517383575439453},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07243424654006958}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7610001564025879},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6611286997795105},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6480824947357178},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.6179494857788086},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.6103761196136475},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6101497411727905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47975099086761475},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4696238338947296},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4308955669403076},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.4225386381149292},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42120349407196045},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41461181640625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34517383575439453},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07243424654006958},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W93016980","https://openalex.org/W652269744","https://openalex.org/W870084106","https://openalex.org/W1492420801","https://openalex.org/W1522301498","https://openalex.org/W1703030490","https://openalex.org/W1998623809","https://openalex.org/W2044913453","https://openalex.org/W2070148066","https://openalex.org/W2077071968","https://openalex.org/W2092961325","https://openalex.org/W2097117768","https://openalex.org/W2098411764","https://openalex.org/W2117539524","https://openalex.org/W2123024445","https://openalex.org/W2124033848","https://openalex.org/W2128532956","https://openalex.org/W2134270519","https://openalex.org/W2153579005","https://openalex.org/W2157133710","https://openalex.org/W2169153112","https://openalex.org/W2171061940","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2250646737","https://openalex.org/W2289084343","https://openalex.org/W2334493732","https://openalex.org/W2398118205","https://openalex.org/W2405223529","https://openalex.org/W2552383788","https://openalex.org/W2594833348","https://openalex.org/W2611632661","https://openalex.org/W2739770654","https://openalex.org/W2751862348","https://openalex.org/W2768228940","https://openalex.org/W2772366472","https://openalex.org/W2783837693","https://openalex.org/W2798451704","https://openalex.org/W2883124384","https://openalex.org/W2887567284","https://openalex.org/W2889587173","https://openalex.org/W2910453440","https://openalex.org/W2962714319","https://openalex.org/W2962762077","https://openalex.org/W2962898354","https://openalex.org/W2962903908","https://openalex.org/W2963283377","https://openalex.org/W2963325056","https://openalex.org/W2963466847","https://openalex.org/W2963499153","https://openalex.org/W2963538198","https://openalex.org/W2963545832","https://openalex.org/W2963955422","https://openalex.org/W2963960318","https://openalex.org/W2963988212","https://openalex.org/W2964086552","https://openalex.org/W2964105864","https://openalex.org/W2964121744","https://openalex.org/W2964162033","https://openalex.org/W2964248207","https://openalex.org/W2964344823","https://openalex.org/W2979402357","https://openalex.org/W2979728922","https://openalex.org/W3010805239","https://openalex.org/W3100093508","https://openalex.org/W3143107425","https://openalex.org/W4232886157","https://openalex.org/W4285719527","https://openalex.org/W4294170691","https://openalex.org/W6600609147","https://openalex.org/W6603820874","https://openalex.org/W6631190155","https://openalex.org/W6637646422","https://openalex.org/W6678360021","https://openalex.org/W6678470764","https://openalex.org/W6682691769","https://openalex.org/W6740580305","https://openalex.org/W6743520202","https://openalex.org/W6746240808","https://openalex.org/W6749074686","https://openalex.org/W6754073506","https://openalex.org/W6754700304"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W4324119766","https://openalex.org/W2105228010"],"abstract_inverted_index":{"Zero-shot":[0],"Learning":[1],"(ZSL)":[2],"aims":[3],"to":[4,8,46,58,89],"learn":[5],"a":[6,31,38,104,120,128],"classifier":[7],"recognize":[9],"unseen":[10],"categories":[11],"without":[12],"training":[13],"samples.":[14],"Most":[15],"ZSL":[16],"works":[17],"based":[18,67],"on":[19,68,152],"embedding":[20,169],"models":[21,72],"handle":[22],"the":[23,27,47,52,82,91,98,132,137,140,146,165],"visual":[24],"space":[25,29,34],"and":[26,35,70,80,143,155],"semantic":[28,101],"through":[30],"common":[32],"metric":[33,79,123,134],"then":[36],"apply":[37],"simple":[39],"nearest":[40],"neighbor":[41],"search":[42],"which":[43,111,135],"directly":[44],"leads":[45],"hubness":[48,92],"problem,":[49],"one":[50],"of":[51,55],"main":[53],"challenges":[54],"ZSL.":[56,95],"Contrary":[57],"recent":[59],"works,":[60],"whose":[61],"conclusions":[62],"about":[63,139],"hubs":[64,114],"are":[65],"drawn":[66],"Euclidean":[69],"specific":[71],"like":[73],"ridge":[74],"regression,":[75],"we":[76,107,126],"adopt":[77],"cosine":[78,86,122,133],"for":[81],"first":[83],"time":[84],"prove":[85],"is":[87],"model-agnostic":[88],"alleviate":[90],"problem":[93],"in":[94],"Assuming":[96],"that":[97,113,160],"normalized":[99],"mapped":[100],"vectors":[102],"follow":[103],"uniform":[105,141],"distribution,":[106],"provide":[108],"theoretical":[109],"analysis":[110],"demonstrates":[112],"can":[115,163],"be":[116],"better":[117],"reduced":[118],"with":[119,131],"higher-dimensional":[121],"space.":[124],"Moreover,":[125],"introduce":[127],"diversity-based":[129],"regularizer":[130],"underpins":[136],"assumption":[138],"distribution":[142],"further":[144],"improves":[145],"model's":[147],"discriminative":[148],"ability.":[149],"Extensive":[150],"experiments":[151],"five":[153],"benchmarks":[154],"large-scale":[156],"Imagenet":[157],"dataset":[158],"show":[159],"our":[161],"method":[162],"improve":[164],"performance,":[166],"surpassing":[167],"previous":[168],"methods":[170],"by":[171],"large":[172],"margins.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}