{"id":"https://openalex.org/W2907859307","doi":"https://doi.org/10.3390/sym11010052","title":"Deep Temporal\u2013Spatial Aggregation for Video-Based Facial Expression Recognition","display_name":"Deep Temporal\u2013Spatial Aggregation for Video-Based Facial Expression Recognition","publication_year":2019,"publication_date":"2019-01-05","ids":{"openalex":"https://openalex.org/W2907859307","doi":"https://doi.org/10.3390/sym11010052","mag":"2907859307"},"language":"en","primary_location":{"id":"doi:10.3390/sym11010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11010052","pdf_url":"https://www.mdpi.com/2073-8994/11/1/52/pdf?version=1546680720","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/11/1/52/pdf?version=1546680720","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023948468","display_name":"Xianzhang Pan","orcid":"https://orcid.org/0000-0003-0469-7178"},"institutions":[{"id":"https://openalex.org/I82760581","display_name":"Taizhou University","ror":"https://ror.org/04fzhyx73","country_code":"CN","type":"education","lineage":["https://openalex.org/I82760581"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianzhang Pan","raw_affiliation_strings":["Institute of Intelligent Information Processing, Taizhou University, Taizhou 318000, China"],"raw_orcid":"https://orcid.org/0000-0003-0469-7178","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Taizhou University, Taizhou 318000, China","institution_ids":["https://openalex.org/I82760581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051503647","display_name":"Wenping Guo","orcid":"https://orcid.org/0000-0002-0405-1775"},"institutions":[{"id":"https://openalex.org/I82760581","display_name":"Taizhou University","ror":"https://ror.org/04fzhyx73","country_code":"CN","type":"education","lineage":["https://openalex.org/I82760581"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenping Guo","raw_affiliation_strings":["Institute of Intelligent Information Processing, Taizhou University, Taizhou 318000, China"],"raw_orcid":"https://orcid.org/0000-0002-0405-1775","affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Taizhou University, Taizhou 318000, China","institution_ids":["https://openalex.org/I82760581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048402590","display_name":"Xiaoying Guo","orcid":"https://orcid.org/0000-0002-8560-4676"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoying Guo","raw_affiliation_strings":["School of Software Engineering, Institute of Big Data Science and Industry, Taiyuan University, Shanxi 030006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Institute of Big Data Science and Industry, Taiyuan University, Shanxi 030006, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086655207","display_name":"Wenshu Li","orcid":"https://orcid.org/0000-0001-8612-7907"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenshu Li","raw_affiliation_strings":["College of information science and technology, Zhejiang Sci-Tech University, Hangzhou 310018, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of information science and technology, Zhejiang Sci-Tech University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050220280","display_name":"Junjie Xu","orcid":"https://orcid.org/0000-0002-1549-693X"},"institutions":[{"id":"https://openalex.org/I28813325","display_name":"Civil Aviation University of China","ror":"https://ror.org/03je71k37","country_code":"CN","type":"education","lineage":["https://openalex.org/I28813325"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Xu","raw_affiliation_strings":["College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China","institution_ids":["https://openalex.org/I28813325"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030022647","display_name":"Jinzhao Wu","orcid":"https://orcid.org/0000-0002-8284-6514"},"institutions":[{"id":"https://openalex.org/I167274908","display_name":"Guangxi University for Nationalities","ror":"https://ror.org/0495efn48","country_code":"CN","type":"education","lineage":["https://openalex.org/I167274908"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinzhao Wu","raw_affiliation_strings":["Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Guangxi University for Nationalities, Nanning 530006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Guangxi University for Nationalities, Nanning 530006, China","institution_ids":["https://openalex.org/I167274908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023948468"],"corresponding_institution_ids":["https://openalex.org/I82760581"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.9376,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.85706667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"1","first_page":"52","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9945999979972839,"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":0.9937999844551086,"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":0.8431438207626343},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6874898672103882},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6150081157684326},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5499994158744812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5460566878318787},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5219330787658691},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5040780305862427},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.42825067043304443},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3243890106678009},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14814624190330505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8431438207626343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6874898672103882},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6150081157684326},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5499994158744812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5460566878318787},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5219330787658691},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5040780305862427},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.42825067043304443},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3243890106678009},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14814624190330505},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym11010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11010052","pdf_url":"https://www.mdpi.com/2073-8994/11/1/52/pdf?version=1546680720","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3b799388c0b54390b0d25a6911f262f5","is_oa":true,"landing_page_url":"https://doaj.org/article/3b799388c0b54390b0d25a6911f262f5","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":"Symmetry, Vol 11, Iss 1, p 52 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/11/1/52/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/sym11010052","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym11010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym11010052","pdf_url":"https://www.mdpi.com/2073-8994/11/1/52/pdf?version=1546680720","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2907859307.pdf"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W147964346","https://openalex.org/W1983364832","https://openalex.org/W2019788814","https://openalex.org/W2024868105","https://openalex.org/W2033702744","https://openalex.org/W2066200210","https://openalex.org/W2071249869","https://openalex.org/W2100495367","https://openalex.org/W2106115875","https://openalex.org/W2109933817","https://openalex.org/W2141890865","https://openalex.org/W2150579376","https://openalex.org/W2154504070","https://openalex.org/W2161801094","https://openalex.org/W2163605009","https://openalex.org/W2168692779","https://openalex.org/W2174631459","https://openalex.org/W2179042386","https://openalex.org/W2198512331","https://openalex.org/W2244142460","https://openalex.org/W2268421884","https://openalex.org/W2274202079","https://openalex.org/W2277498883","https://openalex.org/W2279039799","https://openalex.org/W2294427751","https://openalex.org/W2336160298","https://openalex.org/W2412479940","https://openalex.org/W2563167163","https://openalex.org/W2581082139","https://openalex.org/W2581716072","https://openalex.org/W2587128043","https://openalex.org/W2587680097","https://openalex.org/W2600389231","https://openalex.org/W2606933083","https://openalex.org/W2617085328","https://openalex.org/W2620629206","https://openalex.org/W2621864722","https://openalex.org/W2622634640","https://openalex.org/W2681460984","https://openalex.org/W2703895418","https://openalex.org/W2770344288","https://openalex.org/W2771265655","https://openalex.org/W2773597996","https://openalex.org/W2792585368","https://openalex.org/W2799501716","https://openalex.org/W2883486536","https://openalex.org/W2890970224","https://openalex.org/W2901721413","https://openalex.org/W2906075414","https://openalex.org/W2963112684","https://openalex.org/W2963119563","https://openalex.org/W3097096317","https://openalex.org/W3122143620","https://openalex.org/W3122223220","https://openalex.org/W4249022109","https://openalex.org/W6675736572","https://openalex.org/W6733100057","https://openalex.org/W7019210949"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W3026913501","https://openalex.org/W4401096132"],"abstract_inverted_index":{"The":[0,81,132,155],"proposed":[1,153],"method":[2],"has":[3,90,169],"30":[4,87],"streams,":[5],"i.e.,":[6],"15":[7,11],"spatial":[8,15,69,143],"streams":[9,146],"and":[10,48,70,89,120,141,144,163,172],"temporal":[12,20,71,145],"streams.":[13],"Each":[14],"stream":[16,88],"corresponds":[17],"to":[18,35,41,53,67,114,126],"each":[19],"stream.":[21],"Therefore,":[22],"this":[23,108,167],"work":[24],"correlates":[25],"with":[26],"the":[27,42,45,49,55,75,115,121,142,152,174],"symmetry":[28],"concept.":[29],"It":[30],"is":[31,65,99],"a":[32,57,79,85,91],"difficult":[33],"task":[34],"classify":[36],"video-based":[37,103],"facial":[38,62,104],"expression":[39,63,105],"owing":[40],"gap":[43],"between":[44],"visual":[46],"descriptors":[47],"emotions.":[50],"In":[51],"order":[52],"bridge":[54],"gap,":[56],"new":[58],"video":[59,118],"descriptor":[60],"for":[61,102,135],"recognition":[64],"presented":[66],"aggregate":[68],"convolutional":[72],"features":[73,138],"across":[74],"entire":[76,130],"extent":[77],"of":[78],"video.":[80,131],"designed":[82],"framework":[83,98,109,168],"integrates":[84],"state-of-the-art":[86,175],"trainable":[92,101,122],"spatial\u2013temporal":[93,137],"feature":[94],"aggregation":[95],"layer.":[96],"This":[97],"end-to-end":[100],"recognition.":[106],"Thus,":[107],"can":[110,124],"effectively":[111],"avoid":[112],"overfitting":[113],"limited":[116],"emotional":[117],"datasets,":[119],"strategy":[123],"learn":[125],"better":[127],"represent":[128],"an":[129],"different":[133],"schemas":[134],"pooling":[136],"are":[139,147],"investigated,":[140],"best":[148],"aggregated":[149],"by":[150],"utilizing":[151],"method.":[154],"extensive":[156],"experiments":[157],"on":[158],"two":[159],"public":[160],"databases,":[161],"BAUM-1s":[162],"eNTERFACE05,":[164],"show":[165],"that":[166],"promising":[170],"performance":[171],"outperforms":[173],"strategies.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
