{"id":"https://openalex.org/W4416720874","doi":"https://doi.org/10.34133/icomputing.0246","title":"Scalable Audiovisual Masked Autoencoders for Efficient Affective Video Facial Analysis","display_name":"Scalable Audiovisual Masked Autoencoders for Efficient Affective Video Facial Analysis","publication_year":2025,"publication_date":"2025-11-26","ids":{"openalex":"https://openalex.org/W4416720874","doi":"https://doi.org/10.34133/icomputing.0246"},"language":"en","primary_location":{"id":"doi:10.34133/icomputing.0246","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0246","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.34133/icomputing.0246","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuecheng Wu","orcid":"https://orcid.org/0000-0002-6244-0269"},"institutions":[{"id":"https://openalex.org/I4390039265","display_name":"PRG S&Tech (South Korea)","ror":"https://ror.org/02sr2ee22","country_code":null,"type":"company","lineage":["https://openalex.org/I4390039265"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Xuecheng Wu","raw_affiliation_strings":["School of Computer Science and Technology","CHINA"],"raw_orcid":"https://orcid.org/0000-0002-6244-0269","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology","institution_ids":["https://openalex.org/I4390039265"]},{"raw_affiliation_string":"CHINA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102658609","display_name":"Junxiao Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junxiao Xue","raw_affiliation_strings":["Research Center for Space Computing System, Zhejiang Lab, Hangzhou, Zhejiang, China","CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Space Computing System, Zhejiang Lab, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210123185"]},{"raw_affiliation_string":"CHINA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070335966","display_name":"Xinyi Yin","orcid":"https://orcid.org/0000-0001-6369-7069"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]},{"id":"https://openalex.org/I4210094772","display_name":"Henan University of Engineering","ror":"https://ror.org/007wym039","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210094772"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Yin","raw_affiliation_strings":["School of Cyber Science and Engineering, \rZhengzhou University, Zhengzhou, Henan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, \rZhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650","https://openalex.org/I4210094772"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yunyun Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4390039265","display_name":"PRG S&Tech (South Korea)","ror":"https://ror.org/02sr2ee22","country_code":null,"type":"company","lineage":["https://openalex.org/I4390039265"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Yunyun Shi","raw_affiliation_strings":["School of Computer Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology","institution_ids":["https://openalex.org/I4390039265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019642277","display_name":"Liangyu Fu","orcid":"https://orcid.org/0009-0006-6433-7528"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangyu Fu","raw_affiliation_strings":["School of Software, \rNorthwestern Polytechnical University, Xi\u2019an, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, \rNorthwestern Polytechnical University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043360673","display_name":"Danlei Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4390039265","display_name":"PRG S&Tech (South Korea)","ror":"https://ror.org/02sr2ee22","country_code":null,"type":"company","lineage":["https://openalex.org/I4390039265"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Danlei Huang","raw_affiliation_strings":["School of Computer Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology","institution_ids":["https://openalex.org/I4390039265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101600492","display_name":"Yifan Wang","orcid":"https://orcid.org/0000-0003-1663-3120"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Wang","raw_affiliation_strings":["Institute of Advanced Technology, \rUniversity of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Advanced Technology, \rUniversity of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041","https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010524804","display_name":"Zhang Jia","orcid":"https://orcid.org/0000-0002-7107-7545"},"institutions":[{"id":"https://openalex.org/I4390039265","display_name":"PRG S&Tech (South Korea)","ror":"https://ror.org/02sr2ee22","country_code":null,"type":"company","lineage":["https://openalex.org/I4390039265"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Zhang","raw_affiliation_strings":["School of Computer Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology","institution_ids":["https://openalex.org/I4390039265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104206166","display_name":"Jiayu Nie","orcid":"https://orcid.org/0009-0007-9769-2734"},"institutions":[{"id":"https://openalex.org/I4210144143","display_name":"Inspur (China)","ror":"https://ror.org/0474p4r72","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210144143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayu Nie","raw_affiliation_strings":["Inspur Group, Jinan, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inspur Group, Jinan, Shandong, China","institution_ids":["https://openalex.org/I4210144143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005226976","display_name":"Jun Wang","orcid":"https://orcid.org/0009-0005-7914-3091"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Research Center for Space Computing System, Zhejiang Lab, Hangzhou, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Space Computing System, Zhejiang Lab, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I4210123185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.335,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89974305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"5","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.47200000286102295,"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":0.47200000286102295,"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":0.34220001101493835,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1120000034570694,"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/scalability","display_name":"Scalability","score":0.5817999839782715},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5576000213623047},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5318999886512756},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.45500001311302185},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4526999890804291},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4352000057697296},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.43140000104904175},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.42289999127388},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.42149999737739563},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4009000062942505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8077999949455261},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5817999839782715},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5576000213623047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.550599992275238},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5318999886512756},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48919999599456787},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.43140000104904175},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.31610000133514404},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2687999904155731},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.34133/icomputing.0246","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0246","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b870eef1e4d84c429fe8ab263655f113","is_oa":true,"landing_page_url":"https://doaj.org/article/b870eef1e4d84c429fe8ab263655f113","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Intelligent Computing, Vol 5 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.34133/icomputing.0246","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0246","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":126,"referenced_works":["https://openalex.org/W1480583224","https://openalex.org/W1522734439","https://openalex.org/W2006426145","https://openalex.org/W2030931454","https://openalex.org/W2044106642","https://openalex.org/W2139916508","https://openalex.org/W2146334809","https://openalex.org/W2159017231","https://openalex.org/W2161969291","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2239141610","https://openalex.org/W2325939864","https://openalex.org/W2342475039","https://openalex.org/W2426188534","https://openalex.org/W2478411578","https://openalex.org/W2526050071","https://openalex.org/W2604379605","https://openalex.org/W2703895418","https://openalex.org/W2752782242","https://openalex.org/W2803193013","https://openalex.org/W2808631503","https://openalex.org/W2889466822","https://openalex.org/W2894821115","https://openalex.org/W2911617386","https://openalex.org/W2918087949","https://openalex.org/W2958471948","https://openalex.org/W2959639774","https://openalex.org/W2962162344","https://openalex.org/W2962770129","https://openalex.org/W2962934715","https://openalex.org/W2963155035","https://openalex.org/W2963230974","https://openalex.org/W2963383024","https://openalex.org/W2963524571","https://openalex.org/W2964010806","https://openalex.org/W2964051877","https://openalex.org/W2964338223","https://openalex.org/W2977259558","https://openalex.org/W3015598461","https://openalex.org/W3015906487","https://openalex.org/W3024869864","https://openalex.org/W3034751874","https://openalex.org/W3035452548","https://openalex.org/W3035524453","https://openalex.org/W3035682985","https://openalex.org/W3048939150","https://openalex.org/W3080756971","https://openalex.org/W3090471441","https://openalex.org/W3093370878","https://openalex.org/W3094550259","https://openalex.org/W3172353912","https://openalex.org/W3179103990","https://openalex.org/W3190667038","https://openalex.org/W3195543922","https://openalex.org/W3203407300","https://openalex.org/W3206349670","https://openalex.org/W3209059054","https://openalex.org/W4221042956","https://openalex.org/W4224916778","https://openalex.org/W4224932526","https://openalex.org/W4225934279","https://openalex.org/W4225959162","https://openalex.org/W4289665794","https://openalex.org/W4304099113","https://openalex.org/W4304099179","https://openalex.org/W4312292725","https://openalex.org/W4312546627","https://openalex.org/W4312560592","https://openalex.org/W4312722235","https://openalex.org/W4312976151","https://openalex.org/W4313156423","https://openalex.org/W4313639160","https://openalex.org/W4318980730","https://openalex.org/W4361856786","https://openalex.org/W4375869161","https://openalex.org/W4375869346","https://openalex.org/W4376455521","https://openalex.org/W4385767994","https://openalex.org/W4385823321","https://openalex.org/W4386057769","https://openalex.org/W4386065595","https://openalex.org/W4386072021","https://openalex.org/W4386072059","https://openalex.org/W4386075510","https://openalex.org/W4386076656","https://openalex.org/W4386699383","https://openalex.org/W4387968021","https://openalex.org/W4387968043","https://openalex.org/W4387969745","https://openalex.org/W4388189896","https://openalex.org/W4390841144","https://openalex.org/W4390872103","https://openalex.org/W4390874283","https://openalex.org/W4391941146","https://openalex.org/W4392910434","https://openalex.org/W4392910572","https://openalex.org/W4393181080","https://openalex.org/W4394625692","https://openalex.org/W4400527750","https://openalex.org/W4400527853","https://openalex.org/W4400721967","https://openalex.org/W4400911572","https://openalex.org/W4400975545","https://openalex.org/W4401328604","https://openalex.org/W4401387482","https://openalex.org/W4402170672","https://openalex.org/W4402669711","https://openalex.org/W4402726986","https://openalex.org/W4402727913","https://openalex.org/W4402743945","https://openalex.org/W4402753686","https://openalex.org/W4402916290","https://openalex.org/W4402979749","https://openalex.org/W4403713311","https://openalex.org/W4403780501","https://openalex.org/W4403792097","https://openalex.org/W4403792420","https://openalex.org/W4411631963","https://openalex.org/W4413146043","https://openalex.org/W4413147005","https://openalex.org/W4413155927","https://openalex.org/W4415538052","https://openalex.org/W4415540375","https://openalex.org/W4415540935","https://openalex.org/W4415795657"],"related_works":[],"abstract_inverted_index":{"Affective":[0],"video":[1],"facial":[2],"analysis":[3],"(AVFA)":[4],"has":[5,39,51],"emerged":[6],"as":[7],"a":[8,93,116,130,172],"key":[9],"research":[10],"field":[11,19,74],"for":[12,54],"building":[13],"emotion-aware":[14],"intelligent":[15],"systems,":[16],"yet":[17],"this":[18,73],"continues":[20],"to":[21,100,134],"suffer":[22],"from":[23],"limited":[24],"data":[25],"availability.":[26],"In":[27],"recent":[28],"years,":[29],"the":[30,103,153,157,178,210,221],"self-supervised":[31],"learning":[32,59,146,151],"(SSL)":[33],"technique":[34],"of":[35,95,159,212],"masked":[36],"autoencoders":[37],"(MAEs)":[38],"gained":[40],"momentum,":[41],"with":[42,129],"growing":[43],"adaptations":[44],"in":[45,56,72,106],"audiovisual":[46,84,96,144],"contexts.":[47],"While":[48],"scaling":[49,104],"up":[50],"proven":[52],"essential":[53],"breakthroughs":[55],"general":[57],"multimodal":[58],"domains,":[60],"its":[61],"specific":[62],"impact":[63],"on":[64,188],"AVFA":[65,107,194],"remains":[66],"largely":[67],"unexplored.":[68],"Another":[69],"core":[70],"challenge":[71],"is":[75],"capturing":[76],"both":[77],"intra-":[78],"and":[79,122,125,166,216,229],"intermodal":[80],"correlations":[81],"through":[82],"scalable":[83,137],"representations.":[85],"To":[86,162],"tackle":[87],"these":[88,225],"issues,":[89],"we":[90,140,170],"propose":[91],"AVF-MAE++,":[92],"family":[94],"MAE":[97],"models":[98,230],"designed":[99],"efficiently":[101],"investigate":[102],"properties":[105],"while":[108],"enhancing":[109],"cross-modal":[110],"correlation":[111,145,150],"modeling.":[112],"Our":[113,227],"framework":[114],"introduces":[115],"dual":[117],"masking":[118],"strategy":[119],"across":[120,203],"audio":[121],"visual":[123],"modalities":[124],"strengthens":[126],"modality":[127],"encoders":[128],"more":[131],"holistic":[132],"design":[133,222],"better":[135],"support":[136,163],"pretraining.":[138],"Additionally,":[139],"present":[141],"an":[142],"iterative":[143],"module":[147],"that":[148,197],"improves":[149],"within":[152],"SSL":[154],"paradigm,":[155],"addressing":[156],"limitations":[158],"previous":[160],"methods.":[161],"smooth":[164],"adaptation":[165],"reduce":[167],"overfitting":[168],"risks,":[169],"introduce":[171],"progressive":[173],"semantic":[174],"injection":[175],"strategy,":[176],"organizing":[177],"model":[179],"training":[180],"into":[181,220],"3":[182,192],"structured":[183],"stages.":[184],"Extensive":[185],"experiments":[186],"conducted":[187],"17":[189],"datasets,":[190],"covering":[191],"major":[193],"tasks,":[195],"demonstrate":[196],"AVF-MAE++":[198],"achieves":[199],"consistent":[200],"state-of-the-art":[201],"performance":[202],"multiple":[204],"benchmarks.":[205],"Comprehensive":[206],"ablation":[207],"studies":[208],"highlight":[209],"importance":[211],"each":[213],"proposed":[214],"component":[215],"provide":[217],"deeper":[218],"insights":[219],"choices":[223],"driving":[224],"improvements.":[226],"code":[228],"have":[231],"been":[232],"publicly":[233],"released":[234],"at":[235],"Zenodo.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-11-27T00:00:00"}