{"id":"https://openalex.org/W4379806387","doi":"https://doi.org/10.1145/3591106.3592215","title":"ASCS-Reinforcement Learning: A Cascaded Framework for Accurate 3D Hand Pose Estimation","display_name":"ASCS-Reinforcement Learning: A Cascaded Framework for Accurate 3D Hand Pose Estimation","publication_year":2023,"publication_date":"2023-06-08","ids":{"openalex":"https://openalex.org/W4379806387","doi":"https://doi.org/10.1145/3591106.3592215"},"language":"en","primary_location":{"id":"doi:10.1145/3591106.3592215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3591106.3592215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 ACM International Conference on Multimedia Retrieval","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/A5043764123","display_name":"Mingqi Chen","orcid":"https://orcid.org/0000-0002-3650-293X"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingqi Chen","raw_affiliation_strings":["Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062793914","display_name":"Feng Shuang","orcid":"https://orcid.org/0000-0002-4733-4732"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Shuang","raw_affiliation_strings":["Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057147579","display_name":"Shaodong Li","orcid":"https://orcid.org/0000-0002-5034-8721"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaodong Li","raw_affiliation_strings":["Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045772781","display_name":"X. Liu","orcid":"https://orcid.org/0009-0007-7094-7100"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Liu","raw_affiliation_strings":["Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, China","institution_ids":["https://openalex.org/I150807315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043764123"],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":0.3657,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56976726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"335","last_page":"342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.972000002861023,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9574999809265137,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8528608083724976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7772347927093506},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7024738788604736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6799867153167725},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5817558765411377},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5378443598747253},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4746587574481964},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4636361002922058},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4409090578556061},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4328470528125763},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4035980701446533},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3977999687194824},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07203903794288635}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8528608083724976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7772347927093506},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7024738788604736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6799867153167725},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5817558765411377},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5378443598747253},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4746587574481964},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4636361002922058},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4409090578556061},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4328470528125763},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4035980701446533},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3977999687194824},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07203903794288635},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3591106.3592215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3591106.3592215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 ACM International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1365379061","display_name":null,"funder_award_id":"2022JJB170009","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"}],"funders":[{"id":"https://openalex.org/F4320322768","display_name":"Natural Science Foundation of Guangxi Province","ror":null},{"id":"https://openalex.org/F4320329877","display_name":"Bagui Scholars Program of Guangxi Zhuang Autonomous Region","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1927298993","https://openalex.org/W2075156252","https://openalex.org/W2093414253","https://openalex.org/W2341862707","https://openalex.org/W2565729570","https://openalex.org/W2737305288","https://openalex.org/W2750326862","https://openalex.org/W2775725209","https://openalex.org/W2796453247","https://openalex.org/W2796717907","https://openalex.org/W2799191197","https://openalex.org/W2889123596","https://openalex.org/W2905181441","https://openalex.org/W2951006673","https://openalex.org/W2962067162","https://openalex.org/W2963119249","https://openalex.org/W2963950354","https://openalex.org/W2981561950","https://openalex.org/W2997769754","https://openalex.org/W2998383791","https://openalex.org/W3023254696","https://openalex.org/W3035262841","https://openalex.org/W3046996480","https://openalex.org/W3109047546","https://openalex.org/W3117357611","https://openalex.org/W3130500701","https://openalex.org/W3131200446","https://openalex.org/W3186125447","https://openalex.org/W3190514673","https://openalex.org/W4230133199","https://openalex.org/W4234552385","https://openalex.org/W4361757069"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W3089306886","https://openalex.org/W2113785214","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4393563475","https://openalex.org/W4307623796","https://openalex.org/W4394784820"],"abstract_inverted_index":{"3D":[0,60,153],"hand":[1,61,154],"pose":[2,62,155],"estimation":[3,83],"can":[4],"be":[5,25],"achieved":[6],"by":[7],"cascading":[8],"a":[9,14,70,109,118],"feature":[10,15,31,57],"extraction":[11],"module":[12],"and":[13,46,73,124,138,172],"exploitation":[16,44,58,103],"module,":[17],"where":[18,114],"reinforcement":[19],"learning":[20],"(RL)":[21],"is":[22,90],"proved":[23],"to":[24,29,79,93,130],"an":[26,48],"effective":[27],"way":[28],"perform":[30],"exploitation.":[32,101],"This":[33],"paper":[34],"points":[35],"out":[36,129],"the":[37,80,95,132,144,147,158],"prospects":[38],"of":[39,82,134],"improving":[40],"accuracy":[41,149,171],"using":[42,108],"better":[43,100,168],"strategy,":[45,113],"proposes":[47],"Adaptive":[49],"Step-Critic":[50],"Shared":[51],"RL":[52,111],"(ASCS-RL)":[53],"strategy":[54,89,145],"for":[55,99],"accurate":[56],"in":[59,69,150],"estimation.":[63],"Hand":[64],"joint":[65],"features":[66],"are":[67,105,127],"exploited":[68],"multi-task":[71],"manner,":[72],"divided":[74],"into":[75],"two":[76],"groups":[77,116],"according":[78],"distributions":[81],"error.":[84],"An":[85],"RL-based":[86],"adaptive-step":[87],"(AS-RL)":[88],"then":[91],"used":[92],"obtain":[94],"optimal":[96],"step":[97],"size":[98],"The":[102,141],"process":[104],"finally":[106],"performed":[107],"critic-shared":[110],"(CS-RL)":[112],"both":[115],"share":[117],"universal":[119],"critic":[120],"mechanism.":[121],"Ablation":[122],"studies":[123],"extensive":[125],"experiments":[126],"carried":[128],"evaluate":[131],"performance":[133],"ASCS-RL":[135,166],"on":[136,160],"ICVL":[137],"NYU":[139],"datasets.":[140],"results":[142],"show":[143],"achieves":[146],"state-of-the-art":[148],"monocular":[151],"depth-based":[152],"estimation,":[156],"especially":[157],"best":[159],"ICVL.":[161],"Experiments":[162],"also":[163],"validates":[164],"that":[165],"realizes":[167],"tradeoff":[169],"between":[170],"running":[173],"rapidity.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}