{"id":"https://openalex.org/W2981938460","doi":"https://doi.org/10.1145/3347320.3357690","title":"Efficient Spatial Temporal Convolutional Features for Audiovisual Continuous Affect Recognition","display_name":"Efficient Spatial Temporal Convolutional Features for Audiovisual Continuous Affect Recognition","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2981938460","doi":"https://doi.org/10.1145/3347320.3357690","mag":"2981938460"},"language":"en","primary_location":{"id":"doi:10.1145/3347320.3357690","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347320.3357690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop","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/A5100456775","display_name":"Haifeng Chen","orcid":"https://orcid.org/0000-0001-7164-5840"},"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":true,"raw_author_name":"Haifeng Chen","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004802347","display_name":"Yifan Deng","orcid":"https://orcid.org/0000-0003-0704-2388"},"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":"Yifan Deng","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044359235","display_name":"Shiwen Cheng","orcid":null},"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":"Shiwen Cheng","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408455","display_name":"Yixuan Wang","orcid":"https://orcid.org/0000-0001-7837-7666"},"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":"Yixuan Wang","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102021514","display_name":"Dongmei Jiang","orcid":"https://orcid.org/0000-0002-6238-8499"},"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"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Jiang","raw_affiliation_strings":["Northwestern Polytechnical University &amp; PengCheng Laboratory, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University &amp; PengCheng Laboratory, Xi'an, China","institution_ids":["https://openalex.org/I17145004","https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073820422","display_name":"Hichem Sahli","orcid":"https://orcid.org/0000-0002-1774-2970"},"institutions":[{"id":"https://openalex.org/I4210114974","display_name":"IMEC","ror":"https://ror.org/02kcbn207","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I4210114974"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Hichem Sahli","raw_affiliation_strings":["Vrije University Brussel &amp; Interuniversity Microelectronics Centre, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije University Brussel &amp; Interuniversity Microelectronics Centre, Brussels, Belgium","institution_ids":["https://openalex.org/I4210114974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100456775"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":3.8382,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.93462791,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"19","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T11309","display_name":"Music and Audio Processing","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9771000146865845,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7019994258880615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6925985217094421},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5935696959495544},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5918701887130737},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5474187135696411},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.4998776912689209},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48626649379730225},{"id":"https://openalex.org/keywords/affective-computing","display_name":"Affective computing","score":0.4768292009830475},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4159639775753021},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.41312867403030396},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4005011320114136},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07340818643569946}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7019994258880615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6925985217094421},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5935696959495544},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5918701887130737},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5474187135696411},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.4998776912689209},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48626649379730225},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.4768292009830475},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4159639775753021},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.41312867403030396},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4005011320114136},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07340818643569946},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3347320.3357690","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347320.3357690","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1614298861","https://openalex.org/W1871419576","https://openalex.org/W1999042468","https://openalex.org/W2021913835","https://openalex.org/W2037441721","https://openalex.org/W2129106196","https://openalex.org/W2130162821","https://openalex.org/W2171939880","https://openalex.org/W2239141610","https://openalex.org/W2250539671","https://openalex.org/W2346454595","https://openalex.org/W2422305492","https://openalex.org/W2481681431","https://openalex.org/W2513140567","https://openalex.org/W2526050071","https://openalex.org/W2531648894","https://openalex.org/W2544224704","https://openalex.org/W2610961739","https://openalex.org/W2617750261","https://openalex.org/W2703895418","https://openalex.org/W2765291577","https://openalex.org/W2792764867","https://openalex.org/W2891155597","https://openalex.org/W2897337310","https://openalex.org/W2910165986","https://openalex.org/W2915606245","https://openalex.org/W2920964209","https://openalex.org/W2944458161","https://openalex.org/W2949299266","https://openalex.org/W2949650786","https://openalex.org/W2963155035","https://openalex.org/W2964097678","https://openalex.org/W2981619156","https://openalex.org/W2981677410","https://openalex.org/W3182920176"],"related_works":["https://openalex.org/W2029072726","https://openalex.org/W91913183","https://openalex.org/W2936882366","https://openalex.org/W2736893848","https://openalex.org/W2128698257","https://openalex.org/W1544055438","https://openalex.org/W3003450285","https://openalex.org/W2013608943","https://openalex.org/W4399628019","https://openalex.org/W4310841718"],"abstract_inverted_index":{"Affective":[0],"dimension":[1,63,111],"prediction":[2],"from":[3,28,82],"multi-modal":[4],"is":[5,172,189],"becoming":[6],"an":[7],"increasingly":[8],"attractive":[9],"research":[10],"field":[11],"in":[12,65],"artificial":[13],"intelligence":[14],"(AI)":[15],"and":[16,57,74,85,127,156,178,182,193,207,211],"human-computer":[17],"interaction":[18],"(HCI)":[19],".":[20],"Previous":[21],"works":[22],"have":[23,42],"shown":[24],"that":[25,151],"discriminative":[26],"features":[27,56,81,108,155],"multiple":[29],"modalities":[30],"are":[31],"of":[32,104,205],"importance":[33],"to":[34,44,96,132,174],"accurately":[35],"recognize":[36],"emotional":[37,48],"states.":[38],"Recently,":[39],"deep":[40,54,79],"representations":[41],"proved":[43],"be":[45],"effective":[46],"for":[47,61,77,109,123,141,176,180,191,195],"state":[49],"recognition.":[50],"To":[51,100],"investigate":[52],"new":[53],"spatial-temporal":[55,80,107,154],"evaluate":[58,101],"their":[59],"effectiveness":[60,103],"affective":[62,110],"recognition,":[64],"this":[66],"paper,":[67],"we":[68,113,136],"propose:~(1)":[69],"combining":[70],"a":[71,75,89],"pre-trained":[72],"2D-CNN":[73],"1D-CNN":[76],"learning":[78],"video":[83],"images":[84],"audio":[86],"spectrograms;":[87],"and~(2)":[88],"spatial-Temporal":[90],"Graph":[91],"Convolutional":[92],"Networks":[93,120],"(ST-GCN)":[94],"adapted":[95],"facial":[97],"landmarks":[98],"graph.":[99],"the":[102,105,133,138,146,163,166,184,187,199],"proposed":[106,153],"prediction,":[112,125],"propose":[114],"Deep":[115],"Bidirectional":[116],"Long":[117],"Short-Term":[118],"Memory":[119],"(DBLSTM)":[121],"model":[122,158],"single-modality":[124],"early-fusion":[126],"late-fusion":[128],"predictions.":[129],"With":[130],"respect":[131],"liking":[134],"dimension,":[135],"use":[137],"text":[139],"modality":[140],"prediction.":[142],"Experimental":[143],"results,":[144],"on":[145,183,209],"AVEC2019":[147],"CES":[148],"dataset,":[149],"show":[150],"our":[152],"recognition":[157],"obtain":[159],"promising":[160],"results.":[161],"On":[162],"development":[164],"set,":[165,186],"obtained":[167],"concordance":[168],"correlation":[169],"coefficient":[170],"(CCC)":[171],"up":[173],"$0.724$":[175],"arousal":[177,192,210],"$0.705$":[179],"valence,":[181,196,212],"test":[185],"CCC":[188,204],"$0.513$":[190],"$0.515$":[194],"which":[197],"outperform":[198],"baseline":[200],"system":[201],"with":[202],"corresponding":[203],"$0.355$":[206],"$0.468$":[208],"respectively.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
