{"id":"https://openalex.org/W4210418554","doi":"https://doi.org/10.1109/fg52635.2021.9666970","title":"Your \u201cAttention\u201d Deserves Attention: A Self-Diversified Multi-Channel Attention for Facial Action Analysis","display_name":"Your \u201cAttention\u201d Deserves Attention: A Self-Diversified Multi-Channel Attention for Facial Action Analysis","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4210418554","doi":"https://doi.org/10.1109/fg52635.2021.9666970"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9666970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666970","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.12570","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100785313","display_name":"Xiaotian Li","orcid":"https://orcid.org/0000-0002-2051-4581"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaotian Li","raw_affiliation_strings":["Department of Computer Science, State University of New York at Binghamton, New York, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State University of New York at Binghamton, New York, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100319820","display_name":"Zhihua Li","orcid":"https://orcid.org/0000-0001-6564-6927"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhihua Li","raw_affiliation_strings":["Department of Computer Science, State University of New York at Binghamton, New York, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State University of New York at Binghamton, New York, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100663286","display_name":"Huiyuan Yang","orcid":"https://orcid.org/0000-0003-0517-5187"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huiyuan Yang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Texas, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042144640","display_name":"Geran Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Geran Zhao","raw_affiliation_strings":["Department of Mathematical Science, State University of New York at Binghamton, New York, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Science, State University of New York at Binghamton, New York, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100411653","display_name":"Lijun Yin","orcid":"https://orcid.org/0000-0002-0343-7190"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lijun Yin","raw_affiliation_strings":["Department of Computer Science, State University of New York at Binghamton, New York, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State University of New York at Binghamton, New York, USA","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100785313"],"corresponding_institution_ids":["https://openalex.org/I123946342"],"apc_list":null,"apc_paid":null,"fwci":1.7995,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86666667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"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":0.9976000189781189,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7893520593643188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7413299679756165},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6978162527084351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6569374799728394},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5480322241783142},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4829065799713135},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4764545261859894},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4565467834472656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4490637183189392},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4438944458961487},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42809468507766724},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35732877254486084}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7893520593643188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7413299679756165},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6978162527084351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6569374799728394},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5480322241783142},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4829065799713135},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4764545261859894},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4565467834472656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4490637183189392},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4438944458961487},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42809468507766724},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35732877254486084},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fg52635.2021.9666970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666970","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2203.12570","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.12570","pdf_url":"https://arxiv.org/pdf/2203.12570","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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:2203.12570","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.12570","pdf_url":"https://arxiv.org/pdf/2203.12570","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[{"id":"https://openalex.org/G5760726127","display_name":null,"funder_award_id":"CNS-1629898","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1040410175","https://openalex.org/W1603155784","https://openalex.org/W2014185685","https://openalex.org/W2024868105","https://openalex.org/W2045472600","https://openalex.org/W2051297709","https://openalex.org/W2051688810","https://openalex.org/W2103943262","https://openalex.org/W2117539524","https://openalex.org/W2134860945","https://openalex.org/W2137306662","https://openalex.org/W2198512331","https://openalex.org/W2217426128","https://openalex.org/W2244142460","https://openalex.org/W2262249176","https://openalex.org/W2421475762","https://openalex.org/W2470957930","https://openalex.org/W2506506742","https://openalex.org/W2549139847","https://openalex.org/W2589142773","https://openalex.org/W2730601341","https://openalex.org/W2752782242","https://openalex.org/W2789992948","https://openalex.org/W2798583514","https://openalex.org/W2799041689","https://openalex.org/W2799685664","https://openalex.org/W2866634454","https://openalex.org/W2884585870","https://openalex.org/W2888200171","https://openalex.org/W2903991757","https://openalex.org/W2939059980","https://openalex.org/W2962858109","https://openalex.org/W2963092169","https://openalex.org/W2964007075","https://openalex.org/W2964327872","https://openalex.org/W2964350391","https://openalex.org/W2969059826","https://openalex.org/W2982033433","https://openalex.org/W2989722689","https://openalex.org/W2991040477","https://openalex.org/W3001196836","https://openalex.org/W3011227460","https://openalex.org/W3035565904","https://openalex.org/W3038287124","https://openalex.org/W3087345543","https://openalex.org/W3092729344","https://openalex.org/W3094502228","https://openalex.org/W3101614002","https://openalex.org/W3102025332","https://openalex.org/W3105960011","https://openalex.org/W3121847537","https://openalex.org/W3124054989","https://openalex.org/W3128633047","https://openalex.org/W3176327573","https://openalex.org/W4256016028","https://openalex.org/W4287906843","https://openalex.org/W4385245566","https://openalex.org/W6636286539","https://openalex.org/W6677651945","https://openalex.org/W6680591342","https://openalex.org/W6687716273","https://openalex.org/W6692962889","https://openalex.org/W6739901393","https://openalex.org/W6749370440","https://openalex.org/W6753074096","https://openalex.org/W6753412334","https://openalex.org/W6775046890","https://openalex.org/W6780197826","https://openalex.org/W6784333009","https://openalex.org/W6790428460"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2378211422","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Visual":[0],"attention":[1,32,55,61,69,101,114,124,146,155],"has":[2,27,116],"been":[3],"extensively":[4],"studied":[5],"for":[6,153,178,189],"learning":[7,80,115,125],"fine-grained":[8],"features":[9],"in":[10],"both":[11],"facial":[12,37,40,190],"expression":[13,191],"recognition":[14],"(FER)":[15],"and":[16,46,141,148,176,181,187],"Action":[17],"Unit":[18],"(AU)":[19],"detection.":[20],"A":[21],"broad":[22],"range":[23],"of":[24,59,86,100,108,118,144],"previous":[25],"research":[26],"explored":[28],"how":[29],"to":[30,34,56,81,93,137,198],"use":[31],"modules":[33],"localize":[35],"detailed":[36],"parts":[38],"(e,g.":[39],"action":[41],"units),":[42],"learn":[43,47,149],"discriminative":[44],"features,":[45],"inter-class":[48],"correlation.":[49],"However,":[50],"few":[51],"related":[52],"works":[53],"pay":[54],"the":[57,60,83,97,106,139,150,160,199],"robustness":[58],"module":[62],"itself.":[63],"Through":[64],"experiments,":[65],"we":[66,132,158],"found":[67],"neural":[68,145],"maps":[70,75,102,147],"initialized":[71],"with":[72],"different":[73],"feature":[74,95],"yield":[76],"diverse":[77],"representations":[78],"when":[79],"attend":[82],"identical":[84],"Region":[85],"Interest":[87],"(ROI).":[88],"In":[89,129],"other":[90],"words,":[91],"similar":[92],"general":[94],"learning,":[96],"representational":[98,140],"quality":[99],"also":[103],"greatly":[104],"affects":[105],"performance":[107,196],"a":[109,134],"model,":[110],"which":[111,157],"means":[112],"unconstrained":[113],"lots":[117],"randomnesses.":[119],"This":[120],"uncertainty":[121],"lets":[122],"conventional":[123],"fall":[126],"into":[127],"sub-optimal.":[128],"this":[130],"paper,":[131],"propose":[133],"compact":[135],"model":[136],"enhance":[138],"focusing":[142],"power":[143],"\u201cinter-attention\u201d":[151],"correlation":[152],"refined":[154],"maps,":[156],"term":[159],"\u201cSelf-Diversified":[161],"Multi-Channel":[162],"Attention":[163],"Network":[164],"(SMA-Net)\u201d.":[165],"The":[166],"proposed":[167],"method":[168],"is":[169],"evaluated":[170],"on":[171],"two":[172],"benchmark":[173],"databases":[174,183],"(BP4D":[175],"DISFA)":[177],"AU":[179],"detection":[180],"four":[182],"(CK+,":[184],"MMI,":[185],"BU-3DFE,":[186],"BP4D+)":[188],"recognition.":[192],"It":[193],"achieves":[194],"superior":[195],"compared":[197],"state-of-the-art":[200],"methods.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}