{"id":"https://openalex.org/W4388189896","doi":"https://doi.org/10.1145/3581783.3612365","title":"MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression Recognition","display_name":"MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression Recognition","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388189896","doi":"https://doi.org/10.1145/3581783.3612365"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612365","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3581783.3612365","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3581783.3612365","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3581783.3612365","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027572653","display_name":"Licai Sun","orcid":"https://orcid.org/0000-0002-7944-3458"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licai Sun","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7944-3458","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001973434","display_name":"Zheng Lian","orcid":"https://orcid.org/0000-0001-9477-0599"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Lian","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9477-0599","affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395562","display_name":"Bin Liu","orcid":"https://orcid.org/0000-0003-1529-1552"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1529-1552","affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112613657","display_name":"Jianhua Tao","orcid":"https://orcid.org/0000-0002-9344-6428"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Tao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9344-6428","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":71,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6110","last_page":"6121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9993000030517578,"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":0.9993000030517578,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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":0.9965000152587891,"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":0.7963617444038391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.627898633480072},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.623526394367218},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5701999664306641},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5310718417167664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5016014575958252},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.48625648021698},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.46781325340270996},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45965901017189026},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43261927366256714},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3844180405139923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37715572118759155},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.185556560754776},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0851987898349762}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963617444038391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.627898633480072},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.623526394367218},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5701999664306641},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5310718417167664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5016014575958252},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.48625648021698},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.46781325340270996},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45965901017189026},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43261927366256714},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3844180405139923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37715572118759155},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.185556560754776},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0851987898349762},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3612365","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3581783.3612365","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3581783.3612365","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3581783.3612365","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3581783.3612365","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3581783.3612365","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1202467192","display_name":null,"funder_award_id":"U21B2010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1448168285","display_name":null,"funder_award_id":"62276259","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5381013183","display_name":null,"funder_award_id":"61831022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8569810394","display_name":null,"funder_award_id":"62201572","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320318547","display_name":"Baidu","ror":"https://ror.org/03vs3wt56"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388189896.pdf","grobid_xml":"https://content.openalex.org/works/W4388189896.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1520861770","https://openalex.org/W1522734439","https://openalex.org/W1979377847","https://openalex.org/W2030931454","https://openalex.org/W2081112272","https://openalex.org/W2159017231","https://openalex.org/W2164812378","https://openalex.org/W2168692779","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2277498883","https://openalex.org/W2507009361","https://openalex.org/W2546875627","https://openalex.org/W2803193013","https://openalex.org/W2907859307","https://openalex.org/W2925092820","https://openalex.org/W2962934715","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2963820951","https://openalex.org/W2970710980","https://openalex.org/W2977259558","https://openalex.org/W3034633006","https://openalex.org/W3047624172","https://openalex.org/W3093370878","https://openalex.org/W3097075955","https://openalex.org/W3120201000","https://openalex.org/W3175528717","https://openalex.org/W3206349670","https://openalex.org/W4205166102","https://openalex.org/W4221042956","https://openalex.org/W4225568094","https://openalex.org/W4225959162","https://openalex.org/W4297510825","https://openalex.org/W4304099113","https://openalex.org/W4304099179","https://openalex.org/W4312599212","https://openalex.org/W4312976151","https://openalex.org/W4313156423","https://openalex.org/W4313639160","https://openalex.org/W4318980730","https://openalex.org/W4376455521","https://openalex.org/W4382240798","https://openalex.org/W4386065595","https://openalex.org/W4403242122"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W4292947472"],"abstract_inverted_index":{"Dynamic":[0],"facial":[1,113,161],"expression":[2],"recognition":[3],"(DFER)":[4],"is":[5,27],"essential":[6],"to":[7,65,100,116,119],"the":[8,31,68,73,95,101,180,195],"development":[9,69],"of":[10,43,70,197],"intelligent":[11],"and":[12,124,149,199,208,214],"empathetic":[13],"machines.":[14],"Prior":[15],"efforts":[16],"in":[17,35,79,98,106,205],"this":[18,48,206],"field":[19,207],"mainly":[20],"fall":[21],"into":[22],"supervised":[23,139],"learning":[24],"paradigm,":[25],"which":[26,56],"severely":[28],"restricted":[29],"by":[30,39,141],"limited":[32],"labeled":[33],"data":[34,64],"existing":[36],"datasets.":[37],"Inspired":[38],"recent":[40],"unprecedented":[41],"success":[42],"masked":[44],"autoencoders":[45],"(e.g.,":[46,144],"VideoMAE),":[47],"paper":[49],"proposes":[50],"MAE-DFER,":[51],"a":[52,191],"novel":[53],"self-supervised":[54,59,165],"method":[55],"leverages":[57],"large-scale":[58,164],"pre-training":[60],"on":[61,130,147,152],"abundant":[62],"unlabeled":[63],"largely":[66,178],"advance":[67],"DFER.":[71],"Since":[72],"vanilla":[74],"Vision":[75],"Transformer":[76,92],"(ViT)":[77],"employed":[78],"VideoMAE":[80],"requires":[81],"substantial":[82],"computation":[83],"during":[84],"fine-tuning,":[85],"MAE-DFER":[86,108,135,188],"develops":[87],"an":[88],"efficient":[89],"local-global":[90],"interaction":[91],"(LGI-Former)":[93],"as":[94],"encoder.":[96],"Moreover,":[97],"addition":[99],"standalone":[102],"appearance":[103,123],"content":[104],"reconstruction":[105],"VideoMAE,":[107,176],"also":[109],"introduces":[110],"explicit":[111],"temporal":[112],"motion":[114,126],"modeling":[115],"encourage":[117],"LGI-Former":[118],"excavate":[120],"both":[121],"static":[122],"dynamic":[125,160],"information.":[127],"Extensive":[128],"experiments":[129],"six":[131],"datasets":[132],"show":[133],"that":[134,155],"consistently":[136],"outperforms":[137],"state-of-the-art":[138],"methods":[140],"significant":[142],"margins":[143],"+6.30%":[145],"UAR":[146,151],"DFEW":[148],"+8.34%":[150],"MAFW),":[153],"verifying":[154],"it":[156,168],"can":[157,200],"learn":[158],"powerful":[159],"representations":[162],"via":[163],"pre-training.":[166],"Besides,":[167],"has":[169,189],"comparable":[170],"or":[171],"even":[172,209],"better":[173],"performance":[174],"than":[175],"while":[177],"reducing":[179],"computational":[181],"cost":[182],"(about":[183],"38%":[184],"FLOPs).":[185],"We":[186],"believe":[187],"paved":[190],"new":[192],"way":[193],"for":[194],"advancement":[196],"DFER":[198],"inspire":[201],"more":[202],"relevant":[203],"research":[204],"other":[210],"related":[211],"tasks.":[212],"Codes":[213],"models":[215],"are":[216],"publicly":[217],"available":[218],"at":[219],"https://github.com/sunlicai/MAE-DFER.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":23}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}