{"id":"https://openalex.org/W4226487943","doi":"https://doi.org/10.1109/taffc.2022.3156920","title":"Probabilistic Attribute Tree Structured Convolutional Neural Networks for Facial Expression Recognition in the Wild","display_name":"Probabilistic Attribute Tree Structured Convolutional Neural Networks for Facial Expression Recognition in the Wild","publication_year":2022,"publication_date":"2022-03-07","ids":{"openalex":"https://openalex.org/W4226487943","doi":"https://doi.org/10.1109/taffc.2022.3156920"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2022.3156920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2022.3156920","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","raw_type":"journal-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/A5101943688","display_name":"Jie Cai","orcid":"https://orcid.org/0000-0001-6221-0319"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Cai","raw_affiliation_strings":["OPPO US Research Center and Innopeak Technology, Palo Alto, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6221-0319","affiliations":[{"raw_affiliation_string":"OPPO US Research Center and Innopeak Technology, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036993002","display_name":"Zibo Meng","orcid":"https://orcid.org/0000-0001-7299-7290"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zibo Meng","raw_affiliation_strings":["OPPO US Research Center and Innopeak Technology, Palo Alto, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7299-7290","affiliations":[{"raw_affiliation_string":"OPPO US Research Center and Innopeak Technology, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101032370","display_name":"Ahmed Shehab Khan","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Shehab Khan","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337938","display_name":"Zhiyuan Li","orcid":"https://orcid.org/0000-0002-4616-1841"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiyuan Li","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113694767","display_name":"James O\u2019Reilly","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James O\u2019Reilly","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063566469","display_name":"Yan Tong","orcid":"https://orcid.org/0000-0002-6677-8646"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Tong","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.3095,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.97725957,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"14","issue":"3","first_page":"1927","last_page":"1941"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9995999932289124,"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":0.9980999827384949,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7489141821861267},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7048476934432983},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6914049386978149},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6549739837646484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6302263140678406},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5499384999275208},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.5443626642227173},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5431775450706482},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4541444778442383},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.4254753887653351},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.2612072229385376},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14154532551765442}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7489141821861267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7048476934432983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6914049386978149},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6549739837646484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6302263140678406},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5499384999275208},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.5443626642227173},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5431775450706482},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4541444778442383},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.4254753887653351},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2612072229385376},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14154532551765442},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2022.3156920","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2022.3156920","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.5299999713897705,"display_name":"Gender equality"}],"awards":[{"id":"https://openalex.org/G1420178795","display_name":null,"funder_award_id":"IIS-1149787","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":109,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1546411676","https://openalex.org/W1599366772","https://openalex.org/W1614347434","https://openalex.org/W1628791547","https://openalex.org/W1686810756","https://openalex.org/W1965947362","https://openalex.org/W1974210421","https://openalex.org/W1975436731","https://openalex.org/W1975517671","https://openalex.org/W1976840597","https://openalex.org/W1983611821","https://openalex.org/W1986803802","https://openalex.org/W2017405810","https://openalex.org/W2024868105","https://openalex.org/W2035372623","https://openalex.org/W2035941748","https://openalex.org/W2041616772","https://openalex.org/W2060312700","https://openalex.org/W2065379720","https://openalex.org/W2089569859","https://openalex.org/W2102570318","https://openalex.org/W2103943262","https://openalex.org/W2108333036","https://openalex.org/W2117316476","https://openalex.org/W2117539524","https://openalex.org/W2135318893","https://openalex.org/W2139916508","https://openalex.org/W2143899944","https://openalex.org/W2145287260","https://openalex.org/W2156503193","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2223246223","https://openalex.org/W2243226955","https://openalex.org/W2244142460","https://openalex.org/W2245421092","https://openalex.org/W2246249023","https://openalex.org/W2253728219","https://openalex.org/W2283758531","https://openalex.org/W2293804193","https://openalex.org/W2294427751","https://openalex.org/W2295107390","https://openalex.org/W2296694719","https://openalex.org/W2326887180","https://openalex.org/W2341528187","https://openalex.org/W2474166357","https://openalex.org/W2474193198","https://openalex.org/W2520774990","https://openalex.org/W2548780814","https://openalex.org/W2611154248","https://openalex.org/W2614041639","https://openalex.org/W2730601341","https://openalex.org/W2737559518","https://openalex.org/W2738672149","https://openalex.org/W2780309588","https://openalex.org/W2781292787","https://openalex.org/W2798583514","https://openalex.org/W2799118171","https://openalex.org/W2805080735","https://openalex.org/W2884048435","https://openalex.org/W2887057293","https://openalex.org/W2889978276","https://openalex.org/W2891191887","https://openalex.org/W2894217452","https://openalex.org/W2894944581","https://openalex.org/W2896277673","https://openalex.org/W2899771611","https://openalex.org/W2902346685","https://openalex.org/W2902598059","https://openalex.org/W2904483377","https://openalex.org/W2908186737","https://openalex.org/W2913378657","https://openalex.org/W2942109599","https://openalex.org/W2950180292","https://openalex.org/W2955557105","https://openalex.org/W2962749013","https://openalex.org/W2962852342","https://openalex.org/W2962898354","https://openalex.org/W2963112684","https://openalex.org/W2963278610","https://openalex.org/W2963363102","https://openalex.org/W2963466847","https://openalex.org/W2963656735","https://openalex.org/W2963712289","https://openalex.org/W2964140963","https://openalex.org/W2964347177","https://openalex.org/W2965924668","https://openalex.org/W2969985801","https://openalex.org/W2995034616","https://openalex.org/W3003720578","https://openalex.org/W3034504038","https://openalex.org/W3035336958","https://openalex.org/W3101998545","https://openalex.org/W3118947154","https://openalex.org/W4252545733","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6632670727","https://openalex.org/W6637373629","https://openalex.org/W6646484924","https://openalex.org/W6726946684","https://openalex.org/W6735013348","https://openalex.org/W6737023044","https://openalex.org/W6753000030","https://openalex.org/W6753257457","https://openalex.org/W6755106128","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2642127892","https://openalex.org/W2355913164","https://openalex.org/W4205986151","https://openalex.org/W2231516625","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W2998484203","https://openalex.org/W4323520705","https://openalex.org/W2356663679","https://openalex.org/W2169777806"],"abstract_inverted_index":{"Very":[0],"recent":[1],"work":[2],"has":[3],"demonstrated":[4,163],"tremendous":[5],"improvements":[6],"in":[7,78],"facial":[8,17,153],"expression":[9,154],"recognition":[10],"(FER)":[11],"on":[12,26,150,190],"laboratory-controlled":[13],"datasets.":[14],"However,":[15],"recognizing":[16],"expressions":[18],"under":[19],"in-the-wild":[20],"conditions":[21],"still":[22],"remains":[23],"challenging,":[24],"especially":[25],"unseen":[27],"subjects":[28],"due":[29],"to":[30,48,75,85,110,140,174,197],"high":[31],"inter-subject":[32],"variations.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37],"propose":[38],"a":[39,65,79,182],"novel":[40],"Probabilistic":[41],"Attribute":[42],"Tree":[43],"Convolutional":[44],"Neural":[45],"Network":[46],"(PAT-CNN)":[47],"explicitly":[49,178],"deal":[50],"with":[51,68],"large":[52],"intra-class":[53],"variations":[54],"caused":[55],"by":[56,95,127,177],"identity-related":[57,86],"attributes,":[58,87],"e.g.,":[59],"age,":[60],"race,":[61],"and":[62,160],"gender.":[63],"Specifically,":[64],"PAT":[66,71],"module":[67],"an":[69,202],"associated":[70],"loss":[72],"is":[73],"proposed":[74,131,166],"learn":[76],"features":[77,91,100,119],"hierarchical":[80],"tree":[81,111],"structure":[82],"organized":[83],"according":[84],"where":[88],"the":[89,96,130,142,165,169,187,191,198],"final":[90],"are":[92,101,107],"less":[93],"affected":[94],"attributes.":[97,180],"Then,":[98],"expression-related":[99,118],"extracted":[102],"from":[103,123,136],"leaf":[104],"nodes.":[105],"Samples":[106],"probabilistically":[108],"assigned":[109],"nodes":[112],"at":[113],"different":[114],"levels":[115],"such":[116],"that":[117,164],"can":[120,133],"be":[121,134],"learned":[122,135],"all":[124],"samples":[125,139],"weighted":[126],"probabilities.":[128],"Furthermore,":[129],"PAT-CNN":[132,167,185],"limited":[137],"attribute-annotated":[138],"make":[141],"best":[143,170,188],"use":[144],"of":[145,204,206],"available":[146],"data.":[147],"Experimental":[148],"results":[149],"four":[151],"spontaneous":[152],"datasets,":[155],"i.e.,":[156],"RAF-DB,":[157],"SFEW,":[158],"ExpW,":[159],"FER-2013,":[161],"have":[162],"achieves":[168,186],"performance":[171,189],"when":[172,195],"compared":[173,196],"state-of-the-art":[175,199],"methods":[176,200],"modeling":[179],"Impressively,":[181],"single":[183],"model":[184],"SFEW":[192],"test":[193],"dataset":[194],"using":[201],"ensemble":[203],"hundreds":[205],"CNNs.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
