{"id":"https://openalex.org/W2962815362","doi":"https://doi.org/10.1109/icmew.2017.8026283","title":"Skeleton boxes: Solving skeleton based action detection with a single deep convolutional neural network","display_name":"Skeleton boxes: Solving skeleton based action detection with a single deep convolutional neural network","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2962815362","doi":"https://doi.org/10.1109/icmew.2017.8026283","mag":"2962815362"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2017.8026283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","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/A5114375869","display_name":"Bo Li","orcid":"https://orcid.org/0009-0003-4088-1578"},"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":"Bo Li","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077493861","display_name":"Huahui Chen","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":"Huahui Chen","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100773463","display_name":"Yucheng Chen","orcid":"https://orcid.org/0000-0001-7373-0563"},"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":"Yucheng Chen","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036202579","display_name":"Yuchao Dai","orcid":"https://orcid.org/0000-0002-4432-7406"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuchao Dai","raw_affiliation_strings":["Research School of Engineering, Australian National University, Australia"],"affiliations":[{"raw_affiliation_string":"Research School of Engineering, Australian National University, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086729425","display_name":"Mingyi He","orcid":"https://orcid.org/0000-0003-2051-6955"},"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":"Mingyi He","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5114375869"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.9102,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.84453131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976999759674072,"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":0.9973000288009644,"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/skeleton","display_name":"Skeleton (computer programming)","score":0.8951478004455566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8003678917884827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.780853807926178},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6702620983123779},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6490893363952637},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5903597474098206},{"id":"https://openalex.org/keywords/human-skeleton","display_name":"Human skeleton","score":0.5777026414871216},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4847673773765564},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4653184413909912},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45609816908836365},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44150933623313904},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4391905963420868}],"concepts":[{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.8951478004455566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8003678917884827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.780853807926178},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6702620983123779},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6490893363952637},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5903597474098206},{"id":"https://openalex.org/C2777846634","wikidata":"https://www.wikidata.org/wiki/Q9621","display_name":"Human skeleton","level":2,"score":0.5777026414871216},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4847673773765564},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4653184413909912},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45609816908836365},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44150933623313904},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4391905963420868},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2017.8026283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W846669277","https://openalex.org/W1950788856","https://openalex.org/W2155893237","https://openalex.org/W2307035320","https://openalex.org/W2313903725","https://openalex.org/W2341313195","https://openalex.org/W2415469094","https://openalex.org/W2510185399","https://openalex.org/W2550687635","https://openalex.org/W2556782416","https://openalex.org/W2601271987","https://openalex.org/W2950568498","https://openalex.org/W2952587893","https://openalex.org/W2963364380","https://openalex.org/W2964134613","https://openalex.org/W3106250896","https://openalex.org/W6640754710","https://openalex.org/W6698200468","https://openalex.org/W6704032731","https://openalex.org/W6729791593","https://openalex.org/W6730028046","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2953562271","https://openalex.org/W1979723775","https://openalex.org/W2126881935","https://openalex.org/W4312993112","https://openalex.org/W2784535632","https://openalex.org/W2347221702","https://openalex.org/W3209135759","https://openalex.org/W41889997","https://openalex.org/W2348425426","https://openalex.org/W2523395320"],"abstract_inverted_index":{"Action":[0],"recognition":[1,40],"from":[2,30,70],"well-segmented":[3],"3D":[4,19,32],"skeleton":[5,20,33,61,85,101],"video":[6,21,34,62,79,86],"has":[7],"been":[8],"intensively":[9],"studied.":[10],"However,":[11],"due":[12],"to":[13,87],"the":[14,18,23,113,125],"difficulty":[15],"in":[16,91,142],"representing":[17],"and":[22,42,64,96,115,138],"lack":[24],"of":[25,75],"training":[26],"data,":[27],"action":[28,102],"detection":[29,69],"streaming":[31],"still":[35],"lags":[36],"far":[37],"behind":[38],"its":[39],"counterpart":[41],"image-based":[43],"object":[44,68],"detection.":[45,109],"In":[46],"this":[47,55,143],"paper,":[48],"we":[49],"propose":[50],"a":[51,84,88,92,129],"novel":[52],"approach":[53],"for":[54],"problem,":[56],"which":[57,82],"leverages":[58],"both":[59],"effective":[60],"encoding":[63],"deep":[65],"regression":[66],"based":[67,106],"images.":[71],"Our":[72],"framework":[73],"consists":[74],"two":[76],"parts:":[77],"skeleton-based":[78],"image":[80,90,108],"mapping,":[81],"encodes":[83],"color":[89],"temporal":[93],"preserving":[94],"way,":[95],"an":[97],"end-to-end":[98],"trainable":[99],"fast":[100],"detector":[103],"(Skeleton":[104],"Boxes)":[105],"on":[107,112],"Experimental":[110],"results":[111],"latest":[114],"largest":[116],"PKU-MMD":[117],"benchmark":[118],"dataset":[119],"demonstrate":[120],"that":[121],"our":[122,134],"method":[123],"outperforms":[124],"state-of-the-art":[126],"methods":[127],"with":[128],"large":[130],"margin.":[131],"We":[132],"believe":[133],"idea":[135],"would":[136],"inspire":[137],"benefit":[139],"future":[140],"research":[141],"important":[144],"area.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}