{"id":"https://openalex.org/W3143107425","doi":"https://doi.org/10.1109/cvpr.2009.5206594","title":"Learning to detect unseen object classes by between-class attribute transfer","display_name":"Learning to detect unseen object classes by between-class attribute transfer","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W3143107425","doi":"https://doi.org/10.1109/cvpr.2009.5206594","mag":"3143107425"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206594","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","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/A5068085751","display_name":"Christoph H. Lampert","orcid":"https://orcid.org/0000-0001-8622-7887"},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christoph H. Lampert","raw_affiliation_strings":["Max-Planck Institute of Biological Cybernetics, Tubingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max-Planck Institute of Biological Cybernetics, Tubingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041524969","display_name":"Hannes Nickisch","orcid":"https://orcid.org/0000-0003-1604-6647"},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hannes Nickisch","raw_affiliation_strings":["Max-Planck Institute of Biological Cybernetics, Tubingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max-Planck Institute of Biological Cybernetics, Tubingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062835183","display_name":"Stefan Harmeling","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Harmeling","raw_affiliation_strings":["Max-Planck Institute of Biological Cybernetics, Tubingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max-Planck Institute of Biological Cybernetics, Tubingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068085751"],"corresponding_institution_ids":["https://openalex.org/I4210112925"],"apc_list":null,"apc_paid":null,"fwci":13.81,"has_fulltext":false,"cited_by_count":1612,"citation_normalized_percentile":{"value":0.98803112,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"951","last_page":"958"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980000257492065,"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/T10057","display_name":"Face and Expression Recognition","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.7248940467834473},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6630525588989258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6504943370819092},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6317782402038574},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5871106386184692},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.5097810626029968},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42346620559692383},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.361783504486084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29134559631347656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7248940467834473},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6630525588989258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6504943370819092},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6317782402038574},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5871106386184692},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.5097810626029968},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42346620559692383},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.361783504486084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29134559631347656},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2009.5206594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206594","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W1594031697","https://openalex.org/W1676820704","https://openalex.org/W1981692923","https://openalex.org/W1988091915","https://openalex.org/W1988790447","https://openalex.org/W2009606665","https://openalex.org/W2012995668","https://openalex.org/W2025653905","https://openalex.org/W2027994268","https://openalex.org/W2045798786","https://openalex.org/W2062903088","https://openalex.org/W2066690519","https://openalex.org/W2088252278","https://openalex.org/W2097266862","https://openalex.org/W2098411764","https://openalex.org/W2115733720","https://openalex.org/W2119605622","https://openalex.org/W2120419212","https://openalex.org/W2125560515","https://openalex.org/W2131441114","https://openalex.org/W2133006861","https://openalex.org/W2133774033","https://openalex.org/W2134529554","https://openalex.org/W2139427956","https://openalex.org/W2144502914","https://openalex.org/W2145201922","https://openalex.org/W2151103935","https://openalex.org/W2154422044","https://openalex.org/W2154683974","https://openalex.org/W2155853132","https://openalex.org/W2156406284","https://openalex.org/W2157239837","https://openalex.org/W2159680539","https://openalex.org/W2161969291","https://openalex.org/W2164407453","https://openalex.org/W2548695521","https://openalex.org/W2766736793","https://openalex.org/W3014813097","https://openalex.org/W3188864409","https://openalex.org/W6634343353","https://openalex.org/W6674413621","https://openalex.org/W6678800043","https://openalex.org/W6680007464","https://openalex.org/W6682610290","https://openalex.org/W6683380652"],"related_works":["https://openalex.org/W3201126466","https://openalex.org/W4282827391","https://openalex.org/W4386828785","https://openalex.org/W2737719445","https://openalex.org/W3165580226","https://openalex.org/W4239098401","https://openalex.org/W3135401135","https://openalex.org/W2898210368","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,19,37,41,44,78,95,120,136,151,188,234],"problem":[3,79],"of":[4,18,48,50,60,94,99,105,181,195,233],"object":[5,52,86,223],"classification":[6],"when":[7],"training":[8,16,100,156,231],"and":[9,54,67,164],"test":[10],"classes":[11,21,53,141,190],"are":[12,22],"disjoint,":[13],"i.e.":[14],"no":[15],"examples":[17],"target":[20,96,235],"available.":[23],"This":[24],"setup":[25],"has":[26],"hardly":[27],"been":[28,65],"studied":[29],"in":[30,168,191],"computer":[31],"vision":[32],"research,":[33],"but":[34],"it":[35,215],"is":[36,216],"rule":[38],"rather":[39],"than":[40],"exception,":[42],"because":[43],"world":[45],"contains":[46],"tens":[47],"thousands":[49],"different":[51],"for":[55,153],"only":[56],"a":[57,90,154,174,221],"very":[58],"few":[59],"them":[61],"image,":[62],"collections":[63],"have":[64,172],"formed":[66],"annotated":[68],"with":[69,179,203],"suitable":[70],"class":[71],"labels.":[72],"In":[73,158],"this":[74,169],"paper,":[75],"we":[76,171],"tackle":[77],"by":[80,210],"introducing":[81],"attribute-based":[82],"classification.":[83],"It":[84],"performs":[85],"detection":[87,224],"based":[88,145],"on":[89,146],"human-specified":[91],"high-level":[92],"description":[93,103],"objects":[97],"instead":[98],"images.":[101],"The":[102],"consists":[104],"arbitrary":[106],"semantic":[107,201],"attributes,":[108],"like":[109],"shape,":[110],"color":[111],"or":[112],"even":[113],"geographic":[114],"information.":[115],"Because":[116],"such":[117],"properties":[118],"transcend":[119],"specific":[121],"learning":[122,222],"task":[123],"at":[124],"hand,":[125],"they":[126],"can":[127,142],"be":[128,143],"pre-learned,":[129],"e.g.":[130],"from":[131],"image":[132],"datasets":[133],"unrelated":[134],"to":[135,160,165,219],"current":[137],"task.":[138],"Afterwards,":[139],"new":[140,155,175],"detected":[144],"their":[147],"attribute":[148,213],"representation,":[149],"without":[150],"need":[152],"phase.":[157],"order":[159],"evaluate":[161],"our":[162],"method":[163],"facilitate":[166],"research":[167],"area,":[170],"assembled":[173],"large-scale":[176],"dataset,":[177],"\u201cAnimals":[178],"Attributes\u201d,":[180],"over":[182],"30,000":[183],"animal":[184,204],"images":[185,232],"that":[186,209,226],"match":[187],"50":[189],"Osherson's":[192],"classic":[193],"table":[194],"how":[196],"strongly":[197],"humans":[198],"associate":[199],"85":[200],"attributes":[202],"classes.":[205,236],"Our":[206],"experiments":[207],"show":[208],"using":[211],"an":[212],"layer":[214],"indeed":[217],"possible":[218],"build":[220],"system":[225],"does":[227],"not":[228],"require":[229],"any":[230]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":98},{"year":2024,"cited_by_count":122},{"year":2023,"cited_by_count":172},{"year":2022,"cited_by_count":151},{"year":2021,"cited_by_count":149},{"year":2020,"cited_by_count":109},{"year":2019,"cited_by_count":122},{"year":2018,"cited_by_count":106},{"year":2017,"cited_by_count":117},{"year":2016,"cited_by_count":102},{"year":2015,"cited_by_count":91},{"year":2014,"cited_by_count":69},{"year":2013,"cited_by_count":76},{"year":2012,"cited_by_count":42}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}