{"id":"https://openalex.org/W2973889980","doi":"https://doi.org/10.1109/lsp.2019.2942739","title":"Action Machine: Toward Person-Centric Action Recognition in Videos","display_name":"Action Machine: Toward Person-Centric Action Recognition in Videos","publication_year":2019,"publication_date":"2019-09-20","ids":{"openalex":"https://openalex.org/W2973889980","doi":"https://doi.org/10.1109/lsp.2019.2942739","mag":"2973889980"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2942739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2942739","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5100670090","display_name":"Jiagang Zhu","orcid":"https://orcid.org/0000-0002-0419-1743"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiagang Zhu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0419-1743","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108286207","display_name":"Wei Zou","orcid":"https://orcid.org/0000-0003-4215-5361"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zou","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4215-5361","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705530","display_name":"Zheng Zhu","orcid":"https://orcid.org/0000-0002-4435-1692"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4435-1692","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103277559","display_name":"Liang Xu","orcid":"https://orcid.org/0000-0002-6441-4443"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Xu","raw_affiliation_strings":["Horozon Robotics Co., Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Horozon Robotics Co., Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103027472","display_name":"Guan Huang","orcid":"https://orcid.org/0000-0001-5172-9203"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan Huang","raw_affiliation_strings":["Horozon Robotics Co., Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Horozon Robotics Co., Ltd, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5806,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.92118867,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"26","issue":"11","first_page":"1633","last_page":"1637"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9951000213623047,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8496341705322266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7932367324829102},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.737557053565979},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.708284854888916},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6947623491287231},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.685001790523529},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6803638339042664},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.677288293838501},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5651053786277771},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5621023178100586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4979441165924072},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.46454381942749023},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43983641266822815},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30529242753982544},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08959537744522095},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.08335047960281372}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8496341705322266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7932367324829102},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.737557053565979},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.708284854888916},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6947623491287231},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.685001790523529},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6803638339042664},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.677288293838501},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5651053786277771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5621023178100586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4979441165924072},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.46454381942749023},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43983641266822815},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30529242753982544},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08959537744522095},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.08335047960281372},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2019.2942739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2942739","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G2094734267","display_name":null,"funder_award_id":"61773374","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6289661822","display_name":null,"funder_award_id":"2017YFB1300104","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":39,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1836465849","https://openalex.org/W1950788856","https://openalex.org/W2048821851","https://openalex.org/W2054041160","https://openalex.org/W2108598243","https://openalex.org/W2143267104","https://openalex.org/W2156303437","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2490663605","https://openalex.org/W2507009361","https://openalex.org/W2510185399","https://openalex.org/W2578797046","https://openalex.org/W2593146028","https://openalex.org/W2603861860","https://openalex.org/W2605111198","https://openalex.org/W2613570903","https://openalex.org/W2618530766","https://openalex.org/W2618799552","https://openalex.org/W2778523960","https://openalex.org/W2788865504","https://openalex.org/W2796633859","https://openalex.org/W2799211965","https://openalex.org/W2802979841","https://openalex.org/W2906442255","https://openalex.org/W2953352063","https://openalex.org/W2962677524","https://openalex.org/W2963076818","https://openalex.org/W2963091558","https://openalex.org/W2963150697","https://openalex.org/W2963273301","https://openalex.org/W2963524571","https://openalex.org/W2964134613","https://openalex.org/W6600983433","https://openalex.org/W6638667902","https://openalex.org/W6640754710","https://openalex.org/W6682864246","https://openalex.org/W6747795875"],"related_works":["https://openalex.org/W3192357901","https://openalex.org/W3036286480","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W2962677013"],"abstract_inverted_index":{"Existing":[0],"RGB":[1,106],"and":[2,23,37,79,98,108,133],"CNN-based":[3],"methods":[4],"in":[5,43],"video":[6,116],"action":[7,41,62,85,96,117],"recognition":[8,42,97],"mostly":[9],"do":[10],"not":[11],"distinguish":[12],"human":[13,76],"body":[14],"from":[15,91,105],"the":[16,21,66,92,101],"environment,":[17],"thus":[18],"easily":[19],"overfit":[20],"scenes":[22],"objects":[24],"of":[25,95,103],"training":[26,94],"sets.":[27],"In":[28],"this":[29],"work,":[30],"we":[31],"present":[32],"a":[33,73,80],"conceptually":[34],"simple,":[35],"general":[36],"high-performance":[38],"framework":[39],"for":[40,60,75,83],"videos,":[44],"aiming":[45],"at":[46],"person-centric":[47],"modeling.":[48],"The":[49],"method,":[50],"called":[51],"Action":[52,87,128],"Machine,":[53],"is":[54],"based":[55],"on":[56,114],"person":[57],"bounding":[58],"boxes":[59],"instance-level":[61],"analysis.":[63],"It":[64],"extends":[65],"Inflated":[67],"3D":[68],"ConvNet":[69],"(I3D)":[70],"by":[71],"adding":[72],"branch":[74],"pose":[77,99],"estimation":[78],"2D":[81],"CNN":[82],"pose-based":[84],"recognition.":[86],"Machine":[88,129],"can":[89],"benefit":[90],"multi-task":[93],"estimation,":[100],"fusion":[102],"predictions":[104],"images":[107],"poses.":[109],"Experiments":[110],"results":[111],"are":[112],"provided":[113],"trimmed":[115],"datasets,":[118],"NTU":[119],"RGB+D,":[120],"Northwestern":[121],"UCLA":[122],"Multiview":[123],"Action3D,":[124],"MSR":[125],"Daily":[126],"Activity3D.":[127],"achieves":[130],"superior":[131],"performance":[132],"generalizes":[134],"well":[135],"across":[136],"datasets.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}