{"id":"https://openalex.org/W3162872151","doi":"https://doi.org/10.1109/icpr48806.2021.9412126","title":"PEAN: 3D Hand Pose Estimation Adversarial Network","display_name":"PEAN: 3D Hand Pose Estimation Adversarial Network","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162872151","doi":"https://doi.org/10.1109/icpr48806.2021.9412126","mag":"3162872151"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5113867463","display_name":"Linhui Sun","orcid":null},"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"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linhui Sun","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114686064","display_name":"Yifan Zhang","orcid":"https://orcid.org/0000-0002-9190-3509"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":"Yifan Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113012130","display_name":"Jian Cheng","orcid":"https://orcid.org/0000-0002-9805-8870"},"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"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Cheng","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102146587","display_name":"Hanqing Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":"Hanqing Lu","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113867463"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04911765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1251","last_page":"1258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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":0.9991000294685364,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9789999723434448,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8599530458450317},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.8068664073944092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7289899587631226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6633715033531189},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5520294308662415},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5484663844108582},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5277876257896423},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5128157734870911},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46439841389656067},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4489530622959137},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4223536252975464},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39763593673706055},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16605257987976074}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8599530458450317},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8068664073944092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7289899587631226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6633715033531189},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5520294308662415},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5484663844108582},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5277876257896423},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5128157734870911},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46439841389656067},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4489530622959137},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4223536252975464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39763593673706055},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16605257987976074},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G4896922523","display_name":null,"funder_award_id":"61872364,61876182","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1500711968","https://openalex.org/W1702419847","https://openalex.org/W1923747199","https://openalex.org/W1928739709","https://openalex.org/W1950788856","https://openalex.org/W1974700302","https://openalex.org/W1990947293","https://openalex.org/W2023633446","https://openalex.org/W2075156252","https://openalex.org/W2093414253","https://openalex.org/W2099471712","https://openalex.org/W2100642335","https://openalex.org/W2131213558","https://openalex.org/W2172156083","https://openalex.org/W2194775991","https://openalex.org/W2210697964","https://openalex.org/W2214145768","https://openalex.org/W2218414108","https://openalex.org/W2423984454","https://openalex.org/W2466381304","https://openalex.org/W2521041279","https://openalex.org/W2552247836","https://openalex.org/W2587626861","https://openalex.org/W2606627193","https://openalex.org/W2619078928","https://openalex.org/W2737305288","https://openalex.org/W2750326862","https://openalex.org/W2781143029","https://openalex.org/W2796453247","https://openalex.org/W2796717907","https://openalex.org/W2798895895","https://openalex.org/W2799191197","https://openalex.org/W2889123596","https://openalex.org/W2896229066","https://openalex.org/W2897037859","https://openalex.org/W2962067162","https://openalex.org/W2962878605","https://openalex.org/W2963119249","https://openalex.org/W2963328314","https://openalex.org/W2963508807","https://openalex.org/W2963613382","https://openalex.org/W2963637380","https://openalex.org/W2963950354","https://openalex.org/W2970285700","https://openalex.org/W3105217837","https://openalex.org/W4233641747","https://openalex.org/W4295723303","https://openalex.org/W4320013936","https://openalex.org/W6640754710","https://openalex.org/W6736832757","https://openalex.org/W6746154080","https://openalex.org/W6765820408"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4281696776","https://openalex.org/W4387967917","https://openalex.org/W2022566595","https://openalex.org/W4294967731"],"abstract_inverted_index":{"Despite":[0],"recent":[1],"emerging":[2],"research":[3],"attention,":[4],"3D":[5,35,62,94,117,144],"hand":[6,36,69,95,118,171,202],"pose":[7,37,83,119,132,203],"estimation":[8,38,64,103,204],"still":[9],"suffers":[10],"from":[11],"the":[12,50,73,89,92,99,102,106,115,121,152,162,181,186,192,196],"problems":[13],"of":[14,91,142,185],"predicting":[15,170],"inaccurate":[16],"or":[17],"invalid":[18,153],"poses":[19,145,154],"which":[20,42,71,97],"conflict":[21],"with":[22,78,146],"physical":[23],"and":[24,120,149,173,183],"kinematic":[25],"constraints.":[26],"To":[27],"address":[28],"these":[29],"problems,":[30],"we":[31],"propose":[32],"a":[33,61,79,82,166,190],"novel":[34],"adversarial":[39,54,107],"network":[40,65,85],"(PEAN)":[41],"can":[43],"implicitly":[44],"utilize":[45],"such":[46],"constraints":[47,100],"to":[48,67,87,101,113,128,133,176],"regularize":[49],"prediction":[51],"in":[52,169],"an":[53],"learning":[55,108],"framework.":[56],"PEAN":[57,194],"contains":[58],"two":[59],"parts:":[60],"hierarchical":[63,80],"(3DHNet)":[66],"predict":[68],"pose,":[70,96],"decouples":[72],"task":[74],"into":[75],"multiple":[76],"subtasks":[77],"structure;":[81],"discrimination":[84],"(PDNet)":[86],"judge":[88],"reasonableness":[90,184],"estimated":[93,116],"back-propagates":[98],"network.":[104],"During":[105],"process,":[109],"PDNet":[110,175],"is":[111,126,140],"expected":[112,127],"distinguish":[114],"ground":[122],"truth,":[123],"while":[124],"3DHNet":[125,139,164,177],"estimate":[129],"more":[130],"valid":[131],"confuse":[134],"PDNet.":[135],"In":[136],"this":[137],"way,":[138],"capable":[141],"generating":[143],"accurate":[147],"positions":[148],"adaptively":[150],"adjusting":[151],"without":[155],"additional":[156],"prior":[157],"knowledge.":[158],"Experiments":[159],"show":[160],"that":[161],"proposed":[163,193],"does":[165,178],"good":[167],"job":[168],"poses,":[172],"introducing":[174],"further":[179],"improve":[180],"accuracy":[182],"predicted":[187],"results.":[188],"As":[189],"result,":[191],"achieves":[195],"state-of-the-art":[197],"performance":[198],"on":[199],"three":[200],"public":[201],"datasets.":[205]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}