{"id":"https://openalex.org/W3119221111","doi":"https://doi.org/10.1038/s42256-020-00280-0","title":"Estimation of continuous valence and arousal levels from faces in naturalistic conditions","display_name":"Estimation of continuous valence and arousal levels from faces in naturalistic conditions","publication_year":2021,"publication_date":"2021-01-11","ids":{"openalex":"https://openalex.org/W3119221111","doi":"https://doi.org/10.1038/s42256-020-00280-0","mag":"3119221111"},"language":"en","primary_location":{"id":"doi:10.1038/s42256-020-00280-0","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-020-00280-0","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1038/s42256-020-00280-0","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012464516","display_name":"Antoine Toisoul","orcid":"https://orcid.org/0000-0002-3441-1743"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Antoine Toisoul","raw_affiliation_strings":["Samsung AI, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Samsung AI, Cambridge, UK","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006048318","display_name":"Jean Kossaifi","orcid":"https://orcid.org/0000-0002-4445-3429"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jean Kossaifi","raw_affiliation_strings":["Imperial College London, Department of Computing, London, UK","Samsung AI, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, Department of Computing, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Samsung AI, Cambridge, UK","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072822225","display_name":"Adrian Bulat","orcid":"https://orcid.org/0000-0002-3185-4979"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adrian Bulat","raw_affiliation_strings":["Samsung AI, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Samsung AI, Cambridge, UK","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024224610","display_name":"Georgios Tzimiropoulos","orcid":"https://orcid.org/0000-0002-1803-5338"},"institutions":[{"id":"https://openalex.org/I4210117523","display_name":"Samsung (United Kingdom)","ror":"https://ror.org/01w6gjq94","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210117523"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Georgios Tzimiropoulos","raw_affiliation_strings":["Samsung AI, Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Samsung AI, Cambridge, UK","institution_ids":["https://openalex.org/I4210117523"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016033078","display_name":"Maja Panti\u0107","orcid":"https://orcid.org/0000-0002-3620-5986"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maja Pantic","raw_affiliation_strings":["Imperial College London, Department of Computing, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, Department of Computing, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012464516"],"corresponding_institution_ids":["https://openalex.org/I4210117523"],"apc_list":{"value":9750,"currency":"EUR","value_usd":11690},"apc_paid":{"value":9750,"currency":"EUR","value_usd":11690},"fwci":26.612,"has_fulltext":false,"cited_by_count":205,"citation_normalized_percentile":{"value":0.99800017,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"3","issue":"1","first_page":"42","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.995199978351593,"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/sadness","display_name":"Sadness","score":0.7826544046401978},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.7084767818450928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6725552082061768},{"id":"https://openalex.org/keywords/happiness","display_name":"Happiness","score":0.6044262647628784},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.5947241187095642},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.5544885993003845},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.542851448059082},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5236753821372986},{"id":"https://openalex.org/keywords/affective-computing","display_name":"Affective computing","score":0.4934650957584381},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.4898647964000702},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.48676180839538574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44550976157188416},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.38204509019851685},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34786155819892883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3176344037055969},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.19596856832504272},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.12889835238456726}],"concepts":[{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.7826544046401978},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.7084767818450928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6725552082061768},{"id":"https://openalex.org/C2778999518","wikidata":"https://www.wikidata.org/wiki/Q8","display_name":"Happiness","level":2,"score":0.6044262647628784},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.5947241187095642},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.5544885993003845},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.542851448059082},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5236753821372986},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.4934650957584381},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.4898647964000702},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.48676180839538574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44550976157188416},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.38204509019851685},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34786155819892883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3176344037055969},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.19596856832504272},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.12889835238456726},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s42256-020-00280-0","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-020-00280-0","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s42256-020-00280-0","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-020-00280-0","pdf_url":null,"source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1965947362","https://openalex.org/W1990043338","https://openalex.org/W2012614016","https://openalex.org/W2025905516","https://openalex.org/W2037441721","https://openalex.org/W2103903664","https://openalex.org/W2117769553","https://openalex.org/W2146376820","https://openalex.org/W2149628368","https://openalex.org/W2152627593","https://openalex.org/W2165857685","https://openalex.org/W2194775991","https://openalex.org/W2313339984","https://openalex.org/W2346454595","https://openalex.org/W2587982884","https://openalex.org/W2593853439","https://openalex.org/W2626778328","https://openalex.org/W2745497104","https://openalex.org/W2751214333","https://openalex.org/W2785722081","https://openalex.org/W2798536775","https://openalex.org/W2803023299","https://openalex.org/W2807577508","https://openalex.org/W2885466588","https://openalex.org/W2887057293","https://openalex.org/W2897444637","https://openalex.org/W2907374781","https://openalex.org/W2910165986","https://openalex.org/W2913378657","https://openalex.org/W2916322827","https://openalex.org/W2949662773","https://openalex.org/W2956725921","https://openalex.org/W2960563832","https://openalex.org/W2970971581","https://openalex.org/W3007476359","https://openalex.org/W3100470991","https://openalex.org/W3100513545","https://openalex.org/W3104792420","https://openalex.org/W3122081138","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2519456985","https://openalex.org/W1761974557","https://openalex.org/W1991697485","https://openalex.org/W3198870284","https://openalex.org/W2002225084","https://openalex.org/W4321489666","https://openalex.org/W2119012436","https://openalex.org/W2093522521","https://openalex.org/W346645540","https://openalex.org/W2071993326"],"abstract_inverted_index":{"Facial":[0],"affect":[1,142],"analysis":[2],"aims":[3],"to":[4,14,23,125,139],"create":[5],"new":[6],"types":[7],"of":[8,45,49,105,119,150,204,219,223,236,256],"human\u2013computer":[9,233],"interactions":[10],"by":[11,52],"enabling":[12],"computers":[13],"better":[15],"understand":[16],"a":[17,55,89,133,147,167,245,254],"person\u2019s":[18],"emotional":[19,32,69,79,251],"state":[20],"in":[21,109,143,166,185,214],"order":[22],"provide":[24],"ad":[25],"hoc":[26],"help":[27],"and":[28,39,72,102,107,158,163,188,207,231,242,258],"interactions.":[29,234],"Since":[30],"discrete":[31,239],"classes":[33],"(such":[34],"as":[35],"anger,":[36],"happiness,":[37],"sadness":[38],"so":[40],"on)":[41],"are":[42],"not":[43],"representative":[44],"the":[46,68,78,117,202,220],"full":[47],"spectrum":[48,255],"emotions":[50,165,224],"displayed":[51],"humans":[53],"on":[54,61,180,253],"daily":[56],"basis,":[57],"psychologists":[58],"typically":[59],"rely":[60],"dimensional":[62],"measures,":[63],"namely":[64],"valence":[65,106,257],"(how":[66,74],"positive":[67],"display":[70,80],"is)":[71],"arousal":[73,108,259],"calming":[75],"or":[76],"exciting":[77],"looks":[81],"like).":[82],"However,":[83],"while":[84],"estimating":[85],"these":[86,120],"values":[87],"from":[88],"face":[90,156],"is":[91,96,112],"natural":[92],"for":[93,99,173,228],"humans,":[94],"it":[95,123,171],"extremely":[97],"difficult":[98],"computer-based":[100],"systems":[101],"automatic":[103],"estimation":[104],"naturalistic":[110,144,186],"conditions":[111,145,187],"an":[113],"open":[114],"problem.":[115],"Additionally,":[116],"subjectivity":[118],"measures":[121],"makes":[122],"hard":[124],"obtain":[126],"good":[127],"quality":[128],"data.":[129],"Here":[130],"we":[131],"introduce":[132],"novel":[134],"deep":[135],"neural":[136,247],"network":[137,154,248],"architecture":[138],"analyse":[140],"facial":[141],"with":[146],"high":[148],"level":[149],"accuracy.":[151],"The":[152,217],"proposed":[153],"integrates":[155],"alignment":[157],"jointly":[159],"estimates":[160],"both":[161],"categorical":[162],"continuous":[164],"single":[168,246],"pass,":[169],"making":[170],"suitable":[172],"real-time":[174],"applications.":[175],"We":[176,197],"test":[177],"our":[178,191],"method":[179],"three":[181],"challenging":[182],"datasets":[183],"collected":[184],"show":[189],"that":[190,210,249],"approach":[192],"outperforms":[193],"all":[194],"previous":[195],"methods.":[196],"also":[198],"discuss":[199],"caveats":[200],"regarding":[201],"use":[203,244],"this":[205],"tool,":[206],"ethical":[208],"aspects":[209],"must":[211],"be":[212,226],"considered":[213],"its":[215],"application.":[216],"annotation":[218],"visual":[221],"signs":[222],"can":[225],"important":[227],"psychological":[229],"studies":[230],"even":[232],"Instead":[235],"only":[237],"ascribing":[238],"emotions,":[240],"Toisoul":[241],"colleagues":[243],"predicts":[250],"labels":[252],"without":[260],"separate":[261],"face-alignment":[262],"steps.":[263]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":51},{"year":2024,"cited_by_count":51},{"year":2023,"cited_by_count":59},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":11}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
