{"id":"https://openalex.org/W3119225485","doi":"https://doi.org/10.1109/ssci47803.2020.9308342","title":"Action Detection Based on 3D Convolution Neural Network with Channel Attention Mechanism","display_name":"Action Detection Based on 3D Convolution Neural Network with Channel Attention Mechanism","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3119225485","doi":"https://doi.org/10.1109/ssci47803.2020.9308342","mag":"3119225485"},"language":"en","primary_location":{"id":"doi:10.1109/ssci47803.2020.9308342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5114128425","display_name":"Yan Gao","orcid":"https://orcid.org/0009-0008-7502-0467"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Gao","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030642550","display_name":"Huilai Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huilai Liang","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091703383","display_name":"Baodi Liu","orcid":"https://orcid.org/0000-0002-1408-5514"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baodi Liu","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101722534","display_name":"Yanjiang Wang","orcid":"https://orcid.org/0000-0001-9910-7884"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjiang Wang","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114128425"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1626336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"602","last_page":"606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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":0.8324389457702637},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7130549550056458},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7076324224472046},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.654631495475769},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6324663758277893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6226401329040527},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6177238821983337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5843172669410706},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5736450552940369},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5160788893699646},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4222424328327179},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4070886969566345},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0654897689819336}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8324389457702637},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7130549550056458},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7076324224472046},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.654631495475769},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6324663758277893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6226401329040527},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6177238821983337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5843172669410706},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5736450552940369},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5160788893699646},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4222424328327179},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4070886969566345},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0654897689819336},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci47803.2020.9308342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci47803.2020.9308342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522734439","https://openalex.org/W2019370496","https://openalex.org/W2024868105","https://openalex.org/W2105101328","https://openalex.org/W2108333036","https://openalex.org/W2122710056","https://openalex.org/W2470774766","https://openalex.org/W2613718673","https://openalex.org/W2884585870","https://openalex.org/W2922509574","https://openalex.org/W2941531368","https://openalex.org/W2962934715","https://openalex.org/W2963247196","https://openalex.org/W2963420686","https://openalex.org/W2963616706","https://openalex.org/W2964214371","https://openalex.org/W3031696893","https://openalex.org/W4288375408","https://openalex.org/W6620707391","https://openalex.org/W6720429201","https://openalex.org/W6753412334","https://openalex.org/W6761837902","https://openalex.org/W6779450612"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2964954556","https://openalex.org/W3088721469"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"an":[5],"action":[6,120],"detection":[7],"model,":[8],"a":[9],"simple":[10],"yet":[11],"effective":[12],"combination":[13],"of":[14,29,47,96,119],"channel":[15,40],"attention":[16,36],"mechanism":[17],"with":[18],"3D":[19,49],"convolution":[20],"neural":[21],"network,":[22],"by":[23,99],"which":[24],"to":[25,52,92],"enhance":[26,116],"the":[27,33,39,43,56,62,74,80,89,94,104,111,117],"performance":[28,95],"feature":[30,44,76,85],"extraction":[31,45,86],"in":[32,42,79],"video.":[34,81],"Channel":[35],"module":[37],"uses":[38],"information":[41],"process":[46],"our":[48,84,97],"convolutional":[50],"network":[51],"efficaciously":[53],"pick":[54],"out":[55],"features":[57],"that":[58,110],"are":[59],"essential":[60],"for":[61],"task":[63],"and":[64],"suppress":[65],"useless":[66],"ones.":[67],"The":[68],"proposed":[69,112],"model":[70,87],"can":[71,114],"effectively":[72],"promote":[73],"spatiotemporal":[75],"representation":[77],"power":[78],"We":[82],"embed":[83],"into":[88],"R-C3D":[90],"framework":[91],"test":[93],"method":[98,113],"conducting":[100],"comparative":[101],"experiments":[102],"on":[103],"THUMOS'14":[105],"dataset.":[106],"Experimental":[107],"results":[108],"indicate":[109],"authentically":[115],"accuracy":[118],"detection.":[121]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
