{"id":"https://openalex.org/W3115297295","doi":"https://doi.org/10.1109/vcip49819.2020.9301773","title":"Learning the Connectivity: Situational Graph Convolution Network for Facial Expression Recognition","display_name":"Learning the Connectivity: Situational Graph Convolution Network for Facial Expression Recognition","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3115297295","doi":"https://doi.org/10.1109/vcip49819.2020.9301773","mag":"3115297295"},"language":"en","primary_location":{"id":"doi:10.1109/vcip49819.2020.9301773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5001167901","display_name":"Jinzhao Zhou","orcid":"https://orcid.org/0000-0002-6620-604X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinzhao Zhou","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052689516","display_name":"Xingming Zhang","orcid":"https://orcid.org/0000-0002-8139-0156"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingming Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100356115","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0003-2157-0080"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.9529,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78491921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"230","last_page":"234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":1.0,"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":1.0,"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/T11094","display_name":"Face Recognition and Perception","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9969000220298767,"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":0.6989604830741882},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6512190699577332},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6196445822715759},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5910982489585876},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5902543663978577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5026869773864746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4503180682659149},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2972105145454407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6989604830741882},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6512190699577332},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6196445822715759},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5910982489585876},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5902543663978577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5026869773864746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4503180682659149},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2972105145454407},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip49819.2020.9301773","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4399999976158142,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1981918162","https://openalex.org/W1984926403","https://openalex.org/W2103943262","https://openalex.org/W2108445559","https://openalex.org/W2125434646","https://openalex.org/W2134860945","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2345305417","https://openalex.org/W2600389231","https://openalex.org/W2760398086","https://openalex.org/W2767415038","https://openalex.org/W2799638175","https://openalex.org/W2800840848","https://openalex.org/W2884048435","https://openalex.org/W2903991757","https://openalex.org/W2904483377","https://openalex.org/W2940314039","https://openalex.org/W2940457086","https://openalex.org/W2957147054","https://openalex.org/W2962716958","https://openalex.org/W2963252191","https://openalex.org/W2963369114","https://openalex.org/W2963623198","https://openalex.org/W2970851737","https://openalex.org/W2978324563","https://openalex.org/W3101998545","https://openalex.org/W6679033643","https://openalex.org/W6765595226","https://openalex.org/W6768695299"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W4281727072","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2377538627","https://openalex.org/W2107220315","https://openalex.org/W1589637664"],"abstract_inverted_index":{"Previous":[0],"studies":[1],"recognizing":[2],"expressions":[3],"with":[4,96],"facial":[5,12,21,44,52,81,113],"graph":[6,13,26],"topology":[7],"mostly":[8],"use":[9],"a":[10,37,56],"fixed":[11],"structure":[14,27],"established":[15],"by":[16],"the":[17,24,61,70,102,106,117],"physical":[18],"dependencies":[19,50],"among":[20,51],"landmarks.":[22],"However,":[23],"static":[25],"inherently":[28],"lacks":[29],"flexibility":[30],"in":[31,83],"non-standardized":[32],"scenarios.":[33],"This":[34],"paper":[35],"proposes":[36],"dynamic-graph-based":[38],"method":[39],"for":[40],"effective":[41],"and":[42,79,93],"robust":[43],"expression":[45,82],"recognition.":[46],"To":[47],"capture":[48],"action-specific":[49],"components,":[53],"we":[54],"introduce":[55],"link":[57],"inference":[58],"structure,":[59],"called":[60],"Situational":[62,71],"Link":[63],"Generation":[64],"Module":[65],"(SLGM).":[66],"We":[67],"further":[68,115],"propose":[69],"Graph":[72],"Convolution":[73],"Network":[74],"(SGCN)":[75],"to":[76],"automatically":[77],"detect":[78],"recognize":[80],"various":[84],"conditions.":[85],"Experimental":[86],"evaluations":[87],"on":[88,111],"two":[89],"lab-constrained":[90],"datasets,":[91],"CK+":[92],"Oulu,":[94],"along":[95],"an":[97],"in-the-wild":[98],"dataset,":[99],"AFEW,":[100],"show":[101],"superior":[103],"performance":[104],"of":[105,119],"proposed":[107],"method.":[108],"Additional":[109],"experiments":[110],"occluded":[112],"images":[114],"demonstrate":[116],"robustness":[118],"our":[120],"strategy.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}