{"id":"https://openalex.org/W4323338516","doi":"https://doi.org/10.1109/tii.2023.3253188","title":"Attention-Rectified and Texture-Enhanced Cross-Attention Transformer Feature Fusion Network for Facial Expression Recognition","display_name":"Attention-Rectified and Texture-Enhanced Cross-Attention Transformer Feature Fusion Network for Facial Expression Recognition","publication_year":2023,"publication_date":"2023-03-06","ids":{"openalex":"https://openalex.org/W4323338516","doi":"https://doi.org/10.1109/tii.2023.3253188"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2023.3253188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3253188","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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/A5003359872","display_name":"Mingyi Sun","orcid":"https://orcid.org/0000-0003-2293-0818"},"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":"Mingyi Sun","raw_affiliation_strings":["Department of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2293-0818","affiliations":[{"raw_affiliation_string":"Department of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067818534","display_name":"Weigang Cui","orcid":"https://orcid.org/0000-0002-7983-9161"},"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":"Weigang Cui","raw_affiliation_strings":["School of Engineering Medicine, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7983-9161","affiliations":[{"raw_affiliation_string":"School of Engineering Medicine, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333644","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0001-6733-5014"},"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":"Yue Zhang","raw_affiliation_strings":["Department of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6733-5014","affiliations":[{"raw_affiliation_string":"Department of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038148279","display_name":"Shuyue Yu","orcid":"https://orcid.org/0000-0001-6967-7499"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuyue Yu","raw_affiliation_strings":["Beijing Aerospace Measurement and Control Technology Co., Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6967-7499","affiliations":[{"raw_affiliation_string":"Beijing Aerospace Measurement and Control Technology Co., Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022342592","display_name":"Xiaofeng Liao","orcid":"https://orcid.org/0000-0002-3566-8161"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Liao","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-3566-8161","affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380066","display_name":"Bin Hu","orcid":"https://orcid.org/0000-0003-3514-5413"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Hu","raw_affiliation_strings":["Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3514-5413","affiliations":[{"raw_affiliation_string":"Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100421442","display_name":"Yang Li","orcid":"https://orcid.org/0000-0002-1751-1742"},"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":"Yang Li","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1751-1742","affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.5251,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.98368956,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"19","issue":"12","first_page":"11823","last_page":"11832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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":0.995199978351593,"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"}},{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7692376971244812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7244089841842651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6399134397506714},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.6114180088043213},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5332156419754028},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5257079005241394},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.46086418628692627},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.41224637627601624},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4072367250919342},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.14975428581237793}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7692376971244812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7244089841842651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6399134397506714},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.6114180088043213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5332156419754028},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5257079005241394},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.46086418628692627},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.41224637627601624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4072367250919342},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.14975428581237793},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2023.3253188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3253188","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G3966023777","display_name":null,"funder_award_id":"Z220017","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G5787408445","display_name":null,"funder_award_id":"62201023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W2041616772","https://openalex.org/W2250539671","https://openalex.org/W2436394355","https://openalex.org/W2738672149","https://openalex.org/W2745497104","https://openalex.org/W2785095595","https://openalex.org/W2902598059","https://openalex.org/W2982772166","https://openalex.org/W3003720578","https://openalex.org/W3006560451","https://openalex.org/W3007476359","https://openalex.org/W3010526057","https://openalex.org/W3019410392","https://openalex.org/W3035565904","https://openalex.org/W3035783767","https://openalex.org/W3041607159","https://openalex.org/W3094502228","https://openalex.org/W3112113890","https://openalex.org/W3117707723","https://openalex.org/W3118290699","https://openalex.org/W3119833370","https://openalex.org/W3120399736","https://openalex.org/W3122081138","https://openalex.org/W3151130473","https://openalex.org/W3157960931","https://openalex.org/W3157999215","https://openalex.org/W3163086403","https://openalex.org/W3163942116","https://openalex.org/W3165065619","https://openalex.org/W3168997536","https://openalex.org/W3175546442","https://openalex.org/W3186105911","https://openalex.org/W3197634753","https://openalex.org/W3209798173","https://openalex.org/W3214877835","https://openalex.org/W4200189916","https://openalex.org/W4200350537","https://openalex.org/W4205166102","https://openalex.org/W4210729356","https://openalex.org/W4212852978","https://openalex.org/W4214934944","https://openalex.org/W4220887861","https://openalex.org/W4226322639","https://openalex.org/W4226344365","https://openalex.org/W4289860834","https://openalex.org/W4291910522","https://openalex.org/W4292387426","https://openalex.org/W4296558638","https://openalex.org/W4307647624","https://openalex.org/W4312465353","https://openalex.org/W4394645697","https://openalex.org/W6739901393","https://openalex.org/W6784333009","https://openalex.org/W6787906798","https://openalex.org/W6795641562","https://openalex.org/W6864202710"],"related_works":["https://openalex.org/W2055219403","https://openalex.org/W2791313072","https://openalex.org/W3166997759","https://openalex.org/W2794489335","https://openalex.org/W2080437822","https://openalex.org/W2153027217","https://openalex.org/W2855870609","https://openalex.org/W1589677080","https://openalex.org/W1996690921","https://openalex.org/W1509533962"],"abstract_inverted_index":{"Facial":[0],"expression":[1],"recognition":[2,81],"(FER)":[3],"in":[4,14,45,87],"the":[5,21,27,40,50,55,97,123,131,155,187,199,202,233],"wild":[6],"is":[7,112,168,183],"a":[8,79,92,137,162],"challenging":[9],"task":[10],"for":[11],"affective":[12,218],"computing":[13],"human\u2013machine":[15],"interaction":[16],"fields.":[17],"However,":[18],"most":[19,28],"of":[20,31,54,65,126,157,189,201,214],"existing":[22,44,234],"methods":[23,60],"fail":[24],"to":[25,39,78,115,120,141,170,185],"learn":[26],"prominent":[29],"regions":[30],"facial":[32,74],"images":[33,67],"by":[34],"simple":[35],"cross-entropy":[36],"loss":[37],"due":[38],"imbalance":[41],"problem":[42],"commonly":[43],"FER":[46,94],"datasets,":[47],"which":[48,153,182],"limits":[49],"robustness":[51],"and":[52,72,99,129,149,178,227],"interpretability":[53],"model.":[56],"In":[57],"addition,":[58],"these":[59,85],"only":[61],"capture":[62,142],"local":[63,146],"features":[64,144,177,180],"original":[66],"with":[68],"multisize":[69],"shallow":[70],"convolution":[71,110,118],"ignore":[73],"texture":[75,138,143,159,179],"characteristics,":[76],"leading":[77],"suboptimal":[80],"performance.":[82],"To":[83],"address":[84],"issues,":[86],"this":[88],"article,":[89],"we":[90,135],"propose":[91],"novel":[93],"network,":[95],"named":[96],"attention-rectified":[98,109],"texture-enhanced":[100],"cross-attention":[101,163],"transformer":[102,164],"feature":[103,165],"fusion":[104,166],"network":[105],"(AR-TE-CATFFNet).":[106],"Specifically,":[107],"an":[108],"block":[111,140,167],"first":[113],"designed":[114],"assist":[116],"multiple":[117],"heads":[119],"focus":[121],"on":[122,194,216,224,229],"critical":[124],"areas":[125],"human":[127],"faces":[128,219],"improve":[130],"model":[132],"generalization.":[133],"Second,":[134],"investigate":[136],"enhancement":[139],"through":[145],"binary":[147],"pattern":[148],"gray-level":[150],"co-occurrence":[151],"matrix,":[152],"solves":[154],"limitation":[156],"insufficient":[158],"information.":[160],"Finally,":[161],"employed":[169],"deeply":[171],"integrate":[172],"red,":[173],"green,":[174],"blue":[175],"(RGB)":[176],"globally,":[181],"beneficial":[184],"boost":[186],"accuracy":[188],"recognition.":[190],"Competitive":[191],"experimental":[192],"results":[193],"three":[195],"public":[196],"datasets":[197],"validate":[198],"efficacy":[200],"proposed":[203,208],"method,":[204],"indicating":[205],"that":[206],"our":[207],"method":[209],"achieves":[210],"superior":[211],"classification":[212],"performance":[213],"89.50%":[215],"real-world":[217],"database":[220],"(RAF-DB)":[221],"dataset,":[222,226],"65.66%":[223],"AffectNet":[225],"74.84%":[228],"FER2013":[230],"dataset":[231],"against":[232],"methods.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}