{"id":"https://openalex.org/W2165052637","doi":"https://doi.org/10.1109/cvpr.2009.5206605","title":"How far can you get with a modern face recognition test set using only simple features?","display_name":"How far can you get with a modern face recognition test set using only simple features?","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2165052637","doi":"https://doi.org/10.1109/cvpr.2009.5206605","mag":"2165052637"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206605","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":true,"oa_status":"green","oa_url":"https://dspace.mit.edu/bitstream/1721.1/59976/2/Pinto-2009-How%20far%20can%20you%20get%20with%20a%20modern%20face%20recognition%20test%20set%20using%20only%20simple%20features.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111928952","display_name":"Nicolas Pinto","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110987","display_name":"IIT@MIT","ror":"https://ror.org/01wp8zh54","country_code":"US","type":"facility","lineage":["https://openalex.org/I30771326","https://openalex.org/I4210110987"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nicolas Pinto","raw_affiliation_strings":["MIT, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"MIT, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210110987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014769767","display_name":"James J. DiCarlo","orcid":"https://orcid.org/0000-0002-1592-5896"},"institutions":[{"id":"https://openalex.org/I4210110987","display_name":"IIT@MIT","ror":"https://ror.org/01wp8zh54","country_code":"US","type":"facility","lineage":["https://openalex.org/I30771326","https://openalex.org/I4210110987"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James J. DiCarlo","raw_affiliation_strings":["MIT, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"MIT, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210110987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100763986","display_name":"David Cox","orcid":"https://orcid.org/0000-0002-2189-9743"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David D. Cox","raw_affiliation_strings":["Rowland Institute, Harvard, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Rowland Institute, Harvard, Cambridge, MA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111928952"],"corresponding_institution_ids":["https://openalex.org/I4210110987"],"apc_list":null,"apc_paid":null,"fwci":10.1959,"has_fulltext":true,"cited_by_count":196,"citation_normalized_percentile":{"value":0.98324357,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2591","last_page":"2598"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9998999834060669,"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/T10057","display_name":"Face and Expression Recognition","score":0.9998999834060669,"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":0.9986000061035156,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/computer-science","display_name":"Computer science","score":0.7535098791122437},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7032997608184814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.626426637172699},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5876244306564331},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5448264479637146},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5316047668457031},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5277484059333801},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.49351537227630615},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4810329079627991},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.47848671674728394},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45890870690345764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4355345666408539},{"id":"https://openalex.org/keywords/3d-single-object-recognition","display_name":"3D single-object recognition","score":0.4340250492095947},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41451483964920044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09959441423416138},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0780414342880249}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535098791122437},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7032997608184814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.626426637172699},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5876244306564331},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5448264479637146},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5316047668457031},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5277484059333801},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.49351537227630615},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4810329079627991},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.47848671674728394},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45890870690345764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4355345666408539},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.4340250492095947},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41451483964920044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09959441423416138},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0780414342880249},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2009.5206605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206605","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"},{"id":"pmh:oai:dspace.mit.edu:1721.1/59976","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/59976","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/59976/2/Pinto-2009-How%20far%20can%20you%20get%20with%20a%20modern%20face%20recognition%20test%20set%20using%20only%20simple%20features.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/59976","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/59976","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/59976/2/Pinto-2009-How%20far%20can%20you%20get%20with%20a%20modern%20face%20recognition%20test%20set%20using%20only%20simple%20features.pdf","source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[{"score":0.5,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308324","display_name":"McKnight Foundation","ror":"https://ror.org/003ghvj67"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332916","display_name":"Rowland Institute at Harvard","ror":"https://ror.org/03eta9142"},{"id":"https://openalex.org/F4320337350","display_name":"National Eye Institute","ror":"https://ror.org/03wkg3b53"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2165052637.pdf","grobid_xml":"https://content.openalex.org/works/W2165052637.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W1590105591","https://openalex.org/W1602916555","https://openalex.org/W1739260168","https://openalex.org/W1782590233","https://openalex.org/W1992683700","https://openalex.org/W2006793117","https://openalex.org/W2026942141","https://openalex.org/W2031823405","https://openalex.org/W2080942732","https://openalex.org/W2110764733","https://openalex.org/W2122808326","https://openalex.org/W2127691749","https://openalex.org/W2127949964","https://openalex.org/W2134557905","https://openalex.org/W2150772522","https://openalex.org/W2154462399","https://openalex.org/W2154683974","https://openalex.org/W2155904486","https://openalex.org/W2463472390","https://openalex.org/W2652751060","https://openalex.org/W6634343353","https://openalex.org/W6635800824","https://openalex.org/W6637774275","https://openalex.org/W6683181193","https://openalex.org/W6719492630","https://openalex.org/W6739509182","https://openalex.org/W6992491970"],"related_works":["https://openalex.org/W2207218974","https://openalex.org/W2347601237","https://openalex.org/W2110459882","https://openalex.org/W2897995864","https://openalex.org/W4320197069","https://openalex.org/W2096089671","https://openalex.org/W2354597070","https://openalex.org/W1775397219","https://openalex.org/W2200925278","https://openalex.org/W2613077666"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"large":[3],"databases":[4],"of":[5,15,52,113,123,165,195,206],"natural":[6],"images":[7],"have":[8,72],"become":[9],"increasingly":[10],"popular":[11,56],"in":[12,30,55,110,153],"the":[13,74,100,111,124,154,158,163,193,202],"evaluation":[14],"face":[16,59,148,179,208],"and":[17,58],"object":[18,57],"recognition":[19,39,60,149,180],"algorithms.":[20],"However,":[21,85,156],"Pinto":[22,129],"et":[23,130],"al.":[24,131],"previously":[25],"illustrated":[26],"an":[27,36],"inherent":[28],"danger":[29],"using":[31,80,132],"such":[32],"sets,":[33,61,79],"showing":[34],"that":[35,119,182],"extremely":[37],"basic":[38],"system,":[40],"built":[41],"on":[42,63,145,170,176,200],"a":[43,146,177],"trivial":[44],"feature":[45],"set,":[46],"was":[47],"able":[48],"to":[49,89,96,107],"take":[50],"advantage":[51],"low-level":[53,114],"regularities":[54],"performing":[62],"par":[64],"with":[65,162],"many":[66],"state-of-the-art":[67],"systems.":[68],"Recently,":[69],"several":[70],"groups":[71],"raised":[73],"performance":[75,143],"\u201cbar\u201d":[76],"for":[77],"these":[78,92,171],"more":[81,184],"advanced":[82],"classification":[83],"tools.":[84],"it":[86],"is":[87],"difficult":[88],"know":[90],"whether":[91],"improvements":[93,109],"are":[94,105],"due":[95,106],"progress":[97],"towards":[98],"solving":[99],"core":[101],"computational":[102,204],"problem,":[103],"or":[104],"further":[108],"exploitation":[112],"regularities.":[115],"Here,":[116],"we":[117],"show":[118],"even":[120,161],"modest":[121],"optimization":[122],"simple":[125,172],"model":[126],"introduced":[127],"by":[128,188],"modern":[133],"multiple":[134],"kernel":[135],"learning":[136],"(MKL)":[137],"techniques":[138],"once":[139],"again":[140],"yields":[141],"\u201cstate-of-the-art\u201d":[142],"levels":[144],"standard":[147],"set":[150],"(\u201clabeled":[151],"faces":[152],"wild\u201d).":[155],"at":[157],"same":[159],"time,":[160],"inclusion":[164],"MKL":[166],"techniques,":[167],"systems":[168],"based":[169],"features":[173],"still":[174],"fail":[175],"synthetic":[178],"test":[181,197],"includes":[183],"\u201crealistic\u201d":[185],"view":[186],"variation":[187],"design.":[189],"These":[190],"results":[191],"underscore":[192],"importance":[194],"building":[196],"sets":[198],"focussed":[199],"capturing":[201],"central":[203],"challenges":[205],"real-world":[207],"recognition.":[209]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":25},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":33},{"year":2012,"cited_by_count":29}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
