{"id":"https://openalex.org/W4402353355","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651071","title":"VAD-Net: Multidimensional Emotion Recognition from Facial Expression Images","display_name":"VAD-Net: Multidimensional Emotion Recognition from Facial Expression Images","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353355","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651071"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.06377","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060342813","display_name":"Yi Huo","orcid":"https://orcid.org/0000-0002-5104-245X"},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Huo","raw_affiliation_strings":["Beijing Union University,Educational Information Technology, Teachers&#x2019; College,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Union University,Educational Information Technology, Teachers&#x2019; College,Beijing,China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049775437","display_name":"Yun Ge","orcid":"https://orcid.org/0000-0002-2692-5883"},"institutions":[{"id":"https://openalex.org/I114218197","display_name":"Chinese Academy of Social Sciences","ror":"https://ror.org/05bxbmy32","country_code":"CN","type":"facility","lineage":["https://openalex.org/I114218197"]},{"id":"https://openalex.org/I4391012565","display_name":"University of Chinese Academy of Social Sciences","ror":"https://ror.org/03va9g668","country_code":null,"type":"education","lineage":["https://openalex.org/I4391012565"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Ge","raw_affiliation_strings":["University of Chinese Academy of Social Science,Department of Computer Teaching and Research,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Social Science,Department of Computer Teaching and Research,Beijing,China","institution_ids":["https://openalex.org/I114218197","https://openalex.org/I4391012565"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8724,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76478143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T11448","display_name":"Face recognition and analysis","score":0.9929999709129333,"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/T10057","display_name":"Face and Expression Recognition","score":0.9904999732971191,"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/computer-science","display_name":"Computer science","score":0.6688447594642639},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6549595594406128},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5784474611282349},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.5753932595252991},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4723977744579315},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4537799656391144},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.45153293013572693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4431290030479431},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3947643041610718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38835546374320984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6688447594642639},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6549595594406128},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5784474611282349},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.5753932595252991},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4723977744579315},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4537799656391144},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.45153293013572693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4431290030479431},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3947643041610718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38835546374320984},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2512.06377","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.06377","pdf_url":"https://arxiv.org/pdf/2512.06377","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.06377","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.06377","pdf_url":"https://arxiv.org/pdf/2512.06377","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1588992499","https://openalex.org/W1777859530","https://openalex.org/W1981918162","https://openalex.org/W2017798222","https://openalex.org/W2103943262","https://openalex.org/W2552972371","https://openalex.org/W2587982884","https://openalex.org/W2745497104","https://openalex.org/W2782582470","https://openalex.org/W2912185124","https://openalex.org/W3034222740","https://openalex.org/W3042181847","https://openalex.org/W3121114235","https://openalex.org/W3122081138","https://openalex.org/W3157787344","https://openalex.org/W3199229556","https://openalex.org/W3201331188","https://openalex.org/W4200502861","https://openalex.org/W4224256278","https://openalex.org/W4230277160","https://openalex.org/W4281787794","https://openalex.org/W4283275666","https://openalex.org/W4283362310","https://openalex.org/W4285328537","https://openalex.org/W4311633581"],"related_works":["https://openalex.org/W2642127892","https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W2584926856","https://openalex.org/W2162992774","https://openalex.org/W2075935902","https://openalex.org/W4323520705"],"abstract_inverted_index":{"Current":[0],"FER":[1,168],"(Facial":[2],"Expression":[3],"Recognition)":[4],"dataset":[5,188,218],"is":[6,110,133,223],"mostly":[7],"labeled":[8,216],"by":[9,42,136],"emotion":[10,36],"categories,":[11],"such":[12],"as":[13,191,206],"happy,":[14],"angry,":[15],"sad,":[16],"fear,":[17],"disgust,":[18],"surprise,":[19],"and":[20,34,56,97,117,170,219],"neutral":[21],"which":[22,38],"are":[23],"limited":[24],"in":[25,122],"expressiveness.":[26],"However,":[27],"future":[28],"affective":[29],"computing":[30],"requires":[31],"more":[32,95],"comprehensive":[33],"precise":[35],"metrics":[37],"could":[39,106,147,189,204],"be":[40,107,148],"measured":[41,108],"VAD(Valence-Arousal-Dominance)":[43],"multidimension":[44],"parameters.":[45],"To":[46],"address":[47],"this,":[48],"AffectNet":[49],"has":[50],"tried":[51],"to":[52,75,80,93,112,194],"add":[53],"VA":[54],"(Valence":[55],"Arousal)":[57],"information,":[58],"but":[59,109],"still":[60],"lacks":[61],"D(Dominance).":[62],"Thus,":[63],"the":[64,73,130,151,157,200,207],"research":[65,158],"introduces":[66],"VAD":[67,83,145,177,185,196,210,217],"annotation":[68,124,162],"on":[69,90,167,226],"FER2013":[70,187],"dataset,":[71,169],"takes":[72],"initiative":[74],"label":[76],"D(Dominance)":[77,165],"dimension.":[78],"Then,":[79],"further":[81],"improve":[82],"prediction":[84,146,178,220],"accuracy,":[85],"it":[86],"enforces":[87],"orthogonalized":[88,154,180,201],"convolution":[89,139],"regression":[91,126,174,202],"network":[92,175,203],"extract":[94],"diverse":[96],"expressive":[98],"features.":[99],"Experiment":[100],"results":[101,141],"show":[102],"that":[103,143],"D":[104],"dimension":[105,166],"difficult":[111],"obtain":[113],"compared":[114],"with":[115],"V":[116],"A":[118],"dimension,":[119],"no":[120],"matter":[121],"manual":[123],"or":[125],"model":[127],"prediction.":[128],"Furthermore,":[129],"ablation":[131],"test":[132],"carried":[134],"out":[135],"introducing":[137],"orthogonal":[138],"whose":[140],"verifies":[142],"better":[144,173],"achieved":[149],"under":[150],"configuration":[152],"of":[153],"convolution.":[155],"Therefore,":[156],"provides":[159],"an":[160],"initial":[161],"work":[163],"for":[164,176,209],"proposes":[171],"a":[172,192],"through":[179],"operation.":[181],"The":[182,214],"newly":[183,215],"built":[184],"annotated":[186],"act":[190,205],"benchmark":[193],"measure":[195],"multidimensional":[197],"emotions,":[198],"while":[199],"baseline":[208,221],"facial":[211],"expression":[212],"recognition.":[213],"code":[222],"publicly":[224],"available":[225],"Github:":[227],"https://github.com/YeeHoran/VAD-Net.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
