{"id":"https://openalex.org/W3172057956","doi":"https://doi.org/10.1145/3447587.3447596","title":"An Improved Generative Adversarial Network for Micro-expressions based on Multi-label Learning from Action Units","display_name":"An Improved Generative Adversarial Network for Micro-expressions based on Multi-label Learning from Action Units","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3172057956","doi":"https://doi.org/10.1145/3447587.3447596","mag":"3172057956"},"language":"en","primary_location":{"id":"doi:10.1145/3447587.3447596","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","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/A5010783749","display_name":"LI Meng-ya","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mengya Li","raw_affiliation_strings":["Shandong University, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333509","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-7922-3551"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Shandong University, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101554005","display_name":"Wenhui Wei","orcid":"https://orcid.org/0000-0003-3317-662X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Wei","raw_affiliation_strings":["Shandong University, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018607913","display_name":"Xianye Ben","orcid":"https://orcid.org/0000-0001-8083-3501"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianye Ben","raw_affiliation_strings":["Shandong University, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101578019","display_name":"Deqiang Wang","orcid":"https://orcid.org/0000-0003-0003-4406"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deqiang Wang","raw_affiliation_strings":["Shandong University, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5010783749"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61908279,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"59","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9955999851226807,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7566301822662354},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.710865318775177},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6833127737045288},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6318645477294922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5739521980285645},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5667179226875305},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5539963841438293},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5165697336196899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49363791942596436},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4779484272003174},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4772210717201233},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4571530520915985},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.43501368165016174},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42776599526405334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41232746839523315},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.31548017263412476},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3014785349369049}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7566301822662354},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.710865318775177},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6833127737045288},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6318645477294922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5739521980285645},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5667179226875305},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5539963841438293},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5165697336196899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49363791942596436},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4779484272003174},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4772210717201233},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4571530520915985},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.43501368165016174},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42776599526405334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41232746839523315},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31548017263412476},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3014785349369049},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447587.3447596","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1753905863","https://openalex.org/W2125389028","https://openalex.org/W2139916508","https://openalex.org/W2194775991","https://openalex.org/W2342983306","https://openalex.org/W2520707650","https://openalex.org/W2526853616","https://openalex.org/W2527254703","https://openalex.org/W2571743746","https://openalex.org/W2795270851","https://openalex.org/W2805502563","https://openalex.org/W2963092440","https://openalex.org/W2998061714"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W2888032422","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4235873501"],"abstract_inverted_index":{"Micro-expression":[0,16],"is":[1],"a":[2,52,105,110],"spontaneous":[3],"facial":[4,12],"expression":[5],"with":[6,109,131],"short":[7],"duration,":[8],"low":[9,123],"intensity":[10,124],"and":[11,27,128,166],"partial":[13],"action":[14,69,75,107],"units.":[15,70],"recognition":[17,34,140,179],"plays":[18],"an":[19,56],"important":[20],"role":[21],"in":[22,82],"psychological":[23],"diagnosis,":[24],"lie":[25],"detection,":[26],"security":[28],"systems.":[29],"However,":[30],"even":[31],"the":[32,38,47,72,83,113,132,138,147,151,159,169,172],"state-of-the-art":[33,177],"models":[35],"suffer":[36],"from":[37,68],"lack":[39],"of":[40,85,112,119,171],"micro-expression":[41,126,135,139,178],"samples.":[42,136],"In":[43,71],"order":[44],"to":[45,80,92,150],"augment":[46],"training":[48,134,152],"data,":[49],"we":[50],"propose":[51],"new":[53],"method":[54,174],"\u2014":[55],"improved":[57,144],"Generative":[58],"adversarial":[59],"network":[60],"(GAN)":[61],"for":[62,101,125],"micro-expressions":[63],"based":[64],"on":[65,158],"multi-label":[66],"learning":[67],"proposed":[73,173],"model,":[74],"units":[76],"(AUs)":[77],"are":[78],"added":[79],"GAN":[81],"form":[84],"multi-labels.":[86],"The":[87,97,115,155],"designed":[88,98,116],"loss":[89,99,117],"function":[90,100,118],"ensures":[91],"generate":[93],"high":[94,129],"quality":[95],"images.":[96],"video":[102,108],"can":[103,142],"obtain":[104],"smooth":[106],"trajectory":[111],"AU.":[114],"optical":[120],"flow":[121],"guarantees":[122],"generation":[127],"similarity":[130],"original":[133],"Moreover,":[137],"accuracy":[141],"be":[143],"via":[145],"adding":[146],"generated":[148],"samples":[149],"data":[153],"set.":[154],"experimental":[156],"results":[157],"two":[160],"benchmark":[161],"databases":[162],"including":[163],"CASME":[164],"II":[165],"MMEW":[167],"demonstrate":[168],"superiority":[170],"over":[175],"other":[176],"methods.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
