{"id":"https://openalex.org/W4291908387","doi":"https://doi.org/10.1109/icccs55155.2022.9846106","title":"Facial Expression Recognition Based on Visual Transformers and Local Attention Features Network","display_name":"Facial Expression Recognition Based on Visual Transformers and Local Attention Features Network","publication_year":2022,"publication_date":"2022-04-22","ids":{"openalex":"https://openalex.org/W4291908387","doi":"https://doi.org/10.1109/icccs55155.2022.9846106"},"language":"en","primary_location":{"id":"doi:10.1109/icccs55155.2022.9846106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846106","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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/A5110490436","display_name":"Shuang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Zhao","raw_affiliation_strings":["Southwest University,School of Electronic and Information Engineering,Chongqing,China","School of Electronic and Information Engineering, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University,School of Electronic and Information Engineering,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353217","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0002-2270-6827"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Southwest University,School of Electronic and Information Engineering,Chongqing,China","School of Electronic and Information Engineering, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University,School of Electronic and Information Engineering,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031291553","display_name":"Guangyuan Liu","orcid":"https://orcid.org/0000-0002-8058-5947"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyuan Liu","raw_affiliation_strings":["Southwest University,School of Electronic and Information Engineering,Chongqing,China","School of Electronic and Information Engineering, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University,School of Electronic and Information Engineering,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110490436"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":0.6929,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6916996,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"228","last_page":"231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9980999827384949,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.991100013256073,"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":0.7765017747879028},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506550550460815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7042113542556763},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6202283501625061},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5905949473381042},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5705084800720215},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5463663935661316},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.49997568130493164},{"id":"https://openalex.org/keywords/receptive-field","display_name":"Receptive field","score":0.4282609522342682},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.42116236686706543},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35945966839790344},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35619667172431946},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0929330587387085}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7765017747879028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506550550460815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7042113542556763},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6202283501625061},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5905949473381042},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5705084800720215},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5463663935661316},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.49997568130493164},{"id":"https://openalex.org/C19071747","wikidata":"https://www.wikidata.org/wiki/Q1755207","display_name":"Receptive field","level":2,"score":0.4282609522342682},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.42116236686706543},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35945966839790344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35619667172431946},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0929330587387085},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccs55155.2022.9846106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccs55155.2022.9846106","pdf_url":null,"source":{"id":"https://openalex.org/S4363608130","display_name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","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":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2096214539","https://openalex.org/W2194775991","https://openalex.org/W2515770085","https://openalex.org/W2744909235","https://openalex.org/W2745497104","https://openalex.org/W2787524669","https://openalex.org/W2884585870","https://openalex.org/W2889978276","https://openalex.org/W2902298447","https://openalex.org/W2904483377","https://openalex.org/W2948217907","https://openalex.org/W3003720578","https://openalex.org/W3034552680","https://openalex.org/W3035336958","https://openalex.org/W3035783767","https://openalex.org/W3089911443","https://openalex.org/W3094502228","https://openalex.org/W3107730051","https://openalex.org/W3112113890","https://openalex.org/W3122081138","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6661087397","https://openalex.org/W6726453277","https://openalex.org/W6753412334","https://openalex.org/W6766978945","https://openalex.org/W6779629652","https://openalex.org/W6784333009"],"related_works":["https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W2162992774","https://openalex.org/W4323520705","https://openalex.org/W2356663679","https://openalex.org/W2169777806","https://openalex.org/W3027190010"],"abstract_inverted_index":{"The":[0,90],"application":[1],"of":[2,35,140,164],"convolutional":[3,20,46,50],"neural":[4,21,51],"networks(CNNs)":[5],"has":[6,82],"made":[7],"great":[8],"progress":[9],"in":[10,38,48,86],"facial":[11,69,72,126],"expression":[12,73],"recognition":[13,74,131],"(FER).":[14],"However,":[15],"it":[16],"is":[17],"difficult":[18],"for":[19],"networks":[22,52],"to":[23,28,95,128],"learn":[24],"robust":[25],"features":[26],"due":[27],"the":[29,39,42,45,49,64,101,134,153],"complex":[30],"background":[31],"and":[32,61,124,151,160,167],"low":[33],"quality":[34],"face":[36],"images":[37],"wild.":[40],"At":[41],"same":[43,135],"time,":[44],"filters":[47],"rely":[53],"on":[54,117,157],"local":[55,113,125],"neighborhood":[56],"operations,":[57],"lack":[58],"global":[59,97,123],"information,":[60],"cannot":[62],"capture":[63],"long-distance":[65],"dependence":[66],"between":[67],"different":[68],"regions.":[70],"Therefore,":[71],"remains":[75],"a":[76,112,118,137],"challenging":[77],"task.":[78],"Recently,":[79],"vision":[80,119],"transformer(ViT)":[81],"achieved":[83],"remarkable":[84],"performance":[85],"traditional":[87],"classification":[88],"tasks.":[89],"self-attention":[91],"mechanism":[92],"enables":[93],"transformer":[94],"obtain":[96,129],"receptive":[98],"field":[99],"at":[100],"first":[102],"layer,":[103],"greatly":[104],"improving":[105],"feature":[106],"extraction":[107],"ability.":[108],"This":[109],"paper":[110],"proposes":[111],"attention":[114],"network":[115],"based":[116],"transformer(LAViT),":[120],"which":[121],"utilizes":[122],"information":[127],"high":[130],"accuracy.":[132],"Under":[133],"setting,":[136],"large":[138],"number":[139],"experiments":[141],"show":[142],"that":[143],"our":[144],"method":[145],"performs":[146],"better":[147],"than":[148],"other":[149],"methods":[150],"achieves":[152],"most":[154],"advanced":[155],"results":[156],"RAF-DB,":[158],"FERPlus":[159],"AffectNet,":[161],"with":[162],"accuracies":[163],"87.48%,":[165],"88.90%":[166],"63.90%,":[168],"respectively.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
