{"id":"https://openalex.org/W3201943527","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534132","title":"Scene-Perception Graph Convolutional Networks for Human Action Prediction","display_name":"Scene-Perception Graph Convolutional Networks for Human Action Prediction","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201943527","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534132","mag":"3201943527"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5100763092","display_name":"Jian Tao","orcid":"https://orcid.org/0000-0003-4228-6089"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ji'an Tao","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100777697","display_name":"Lu Xu","orcid":"https://orcid.org/0000-0002-8572-9890"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Xu","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090668786","display_name":"Xinyan Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyan Ma","raw_affiliation_strings":["Institute of Control Theory and Control Engineering, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Institute of Control Theory and Control Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060430824","display_name":"Jianyu Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyu Yan","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034840700","display_name":"Kuizhi Mei","orcid":"https://orcid.org/0000-0002-8119-3726"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuizhi Mei","raw_affiliation_strings":["School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100763092"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49424837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9979000091552734,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.993399977684021,"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":0.8239057064056396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7330330610275269},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.641518235206604},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6146517395973206},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.6016367673873901},{"id":"https://openalex.org/keywords/human-skeleton","display_name":"Human skeleton","score":0.5727246403694153},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5353527665138245},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4921237826347351},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42593610286712646},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4222126603126526},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.42002543807029724},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41749969124794006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38187849521636963},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2977546453475952},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11249032616615295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8239057064056396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7330330610275269},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.641518235206604},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6146517395973206},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.6016367673873901},{"id":"https://openalex.org/C2777846634","wikidata":"https://www.wikidata.org/wiki/Q9621","display_name":"Human skeleton","level":2,"score":0.5727246403694153},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5353527665138245},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4921237826347351},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42593610286712646},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4222126603126526},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.42002543807029724},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41749969124794006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38187849521636963},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2977546453475952},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11249032616615295},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534132","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G180409970","display_name":null,"funder_award_id":"62076193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3428205251","display_name":null,"funder_award_id":"2017YFB1301101","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1483019628","https://openalex.org/W1735317348","https://openalex.org/W2101032778","https://openalex.org/W2146055337","https://openalex.org/W2157331557","https://openalex.org/W2194775991","https://openalex.org/W2424778531","https://openalex.org/W2519887557","https://openalex.org/W2613570903","https://openalex.org/W2619947201","https://openalex.org/W2623040213","https://openalex.org/W2896231477","https://openalex.org/W2896588340","https://openalex.org/W2903831537","https://openalex.org/W2940457086","https://openalex.org/W2945143046","https://openalex.org/W2948058585","https://openalex.org/W2962730651","https://openalex.org/W2963076818","https://openalex.org/W2963165299","https://openalex.org/W2964015378","https://openalex.org/W2964134613","https://openalex.org/W2964203186","https://openalex.org/W2976818183","https://openalex.org/W2996835428","https://openalex.org/W3034423770","https://openalex.org/W3099014939","https://openalex.org/W3099128265","https://openalex.org/W3108496296","https://openalex.org/W6726873649","https://openalex.org/W6747795875","https://openalex.org/W6753751772","https://openalex.org/W6756633688","https://openalex.org/W6761067018","https://openalex.org/W6786349491"],"related_works":["https://openalex.org/W2796878614","https://openalex.org/W4367681502","https://openalex.org/W4367591752","https://openalex.org/W4379796555","https://openalex.org/W2999049608","https://openalex.org/W3114238187","https://openalex.org/W2005414443","https://openalex.org/W2996960708","https://openalex.org/W2986215149","https://openalex.org/W3011973369"],"abstract_inverted_index":{"Human":[0],"action":[1,152],"recognition":[2],"and":[3,15,88,107,125,137,151],"prediction":[4,82],"with":[5,42,123,170],"skeleton-based":[6],"data":[7],"has":[8],"been":[9],"widely":[10],"applied":[11],"in":[12,109],"intelligent":[13],"robots":[14],"machine":[16],"vision.":[17],"Current":[18],"advanced":[19],"methods":[20],"mainly":[21],"focus":[22],"on":[23,35,51,85,157],"using":[24],"recurrent":[25],"neural":[26],"network":[27,122],"(RNN)":[28],"to":[29,99,112,130,147],"predict":[30,113,148],"human":[31,44,52,80,89,114,136],"motion":[32],"based":[33,84],"only":[34],"skeleton":[36,105],"data.":[37],"However,":[38],"objects":[39,60,87,108],"that":[40,162],"interact":[41],"the":[43,63,101,110,132,140,171],"body":[45,55],"will":[46],"have":[47],"a":[48,73,93],"great":[49],"impact":[50],"behaviors.":[53],"Extracting":[54],"information":[56],"without":[57],"considering":[58],"environmental":[59],"constraints":[61],"reduces":[62],"accuracy":[64],"of":[65,119],"behavior":[66,81],"prediction.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"propose":[72,92],"scene-perception":[74,94],"architecture,":[75],"which":[76],"implements":[77],"an":[78],"end-to-end":[79],"task":[83],"both":[86],"skeleton.":[90],"We":[91,154],"Graph":[95],"Convolutional":[96],"Network":[97],"(SPGCN)":[98],"formula":[100],"natural":[102],"constraint":[103],"between":[104,135],"nodes":[106],"scene":[111],"postures.":[115],"SPGCN":[116,156],"is":[117,128],"composed":[118],"graph":[120],"convolutional":[121],"scene-aware":[124],"RNN,":[126],"GCN":[127],"used":[129],"learn":[131],"dependence":[133],"relationships":[134],"objects.":[138],"Then,":[139],"learned":[141],"features":[142],"are":[143],"fed":[144],"into":[145],"RNN":[146],"future":[149],"pose":[150],"labels.":[153],"evaluate":[155],"CAD-120":[158],"dataset.":[159],"Experiments":[160],"show":[161],"our":[163],"proposed":[164],"method":[165],"achieves":[166],"promising":[167],"results":[168],"compared":[169],"state-of-the-art":[172],"methods.":[173]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
