{"id":"https://openalex.org/W3005718951","doi":"https://doi.org/10.1109/tip.2020.2972104","title":"A Joint Relationship Aware Neural Network for Single-Image 3D Human Pose Estimation","display_name":"A Joint Relationship Aware Neural Network for Single-Image 3D Human Pose Estimation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3005718951","doi":"https://doi.org/10.1109/tip.2020.2972104","mag":"3005718951"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.2972104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2972104","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://ir.opt.ac.cn/handle/181661/93325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007883693","display_name":"Xiangtao Zheng","orcid":"https://orcid.org/0000-0002-8398-6324"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangtao Zheng","raw_affiliation_strings":["Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101759886","display_name":"Xiumei Chen","orcid":"https://orcid.org/0000-0002-0610-990X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]},{"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":"Xiumei Chen","raw_affiliation_strings":["Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","University of Chinese Academy of Sciences, Beijing, China","Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018824735","display_name":"Xiaoqiang Lu","orcid":"https://orcid.org/0000-0002-7037-5188"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqiang Lu","raw_affiliation_strings":["Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi\u2019an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007883693"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210144662"],"apc_list":null,"apc_paid":null,"fwci":2.7479,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.91932489,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"29","issue":null,"first_page":"4747","last_page":"4758"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"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/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7826910018920898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7303990125656128},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7096980810165405},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.694219708442688},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6523019671440125},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6484706997871399},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6240172386169434},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.583267092704773},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5561935901641846},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5138859748840332},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.49605926871299744},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4395048916339874},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4180610775947571},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15567395091056824},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09430432319641113}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7826910018920898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303990125656128},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7096980810165405},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.694219708442688},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6523019671440125},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6484706997871399},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6240172386169434},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.583267092704773},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5561935901641846},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5138859748840332},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.49605926871299744},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4395048916339874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4180610775947571},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15567395091056824},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09430432319641113},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural 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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.2972104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2972104","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:ir.opt.ac.cn:181661/93325","is_oa":true,"landing_page_url":"http://ir.opt.ac.cn/handle/181661/93325","pdf_url":null,"source":{"id":"https://openalex.org/S4377196962","display_name":"Institutional Repository of Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (Xian Institute of Optics and Precision Mechanics)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210144662","host_organization_name":"Xi'an Institute of Optics and Precision Mechanics","host_organization_lineage":["https://openalex.org/I4210144662"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u671f\u520a\u8bba\u6587"}],"best_oa_location":{"id":"pmh:oai:ir.opt.ac.cn:181661/93325","is_oa":true,"landing_page_url":"http://ir.opt.ac.cn/handle/181661/93325","pdf_url":null,"source":{"id":"https://openalex.org/S4377196962","display_name":"Institutional Repository of Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (Xian Institute of Optics and Precision Mechanics)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210144662","host_organization_name":"Xi'an Institute of Optics and Precision Mechanics","host_organization_lineage":["https://openalex.org/I4210144662"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u671f\u520a\u8bba\u6587"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2926447122","display_name":null,"funder_award_id":"QYZDB-SSW-JSC015","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G3810805587","display_name":null,"funder_award_id":"61806193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5697410714","display_name":null,"funder_award_id":"XAB2017B15","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G6349446410","display_name":null,"funder_award_id":"XAB2017B26","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G7869768529","display_name":null,"funder_award_id":"61772510","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G856301868","display_name":null,"funder_award_id":"61702498","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"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W602397586","https://openalex.org/W1559083155","https://openalex.org/W1943191679","https://openalex.org/W1967554269","https://openalex.org/W2018854916","https://openalex.org/W2029375985","https://openalex.org/W2080873731","https://openalex.org/W2101032778","https://openalex.org/W2119102184","https://openalex.org/W2131494463","https://openalex.org/W2135533529","https://openalex.org/W2413794162","https://openalex.org/W2470673105","https://openalex.org/W2483862638","https://openalex.org/W2515603221","https://openalex.org/W2522527348","https://openalex.org/W2550553598","https://openalex.org/W2554247908","https://openalex.org/W2557698284","https://openalex.org/W2575842049","https://openalex.org/W2583372902","https://openalex.org/W2594105920","https://openalex.org/W2604375920","https://openalex.org/W2612706635","https://openalex.org/W2740103755","https://openalex.org/W2752782242","https://openalex.org/W2753064086","https://openalex.org/W2756050327","https://openalex.org/W2758778552","https://openalex.org/W2781181706","https://openalex.org/W2785641712","https://openalex.org/W2787839673","https://openalex.org/W2791083848","https://openalex.org/W2795089319","https://openalex.org/W2797184202","https://openalex.org/W2798637590","https://openalex.org/W2798646183","https://openalex.org/W2800401531","https://openalex.org/W2804340531","https://openalex.org/W2809890486","https://openalex.org/W2884585870","https://openalex.org/W2892270791","https://openalex.org/W2912747081","https://openalex.org/W2916798096","https://openalex.org/W2922521335","https://openalex.org/W2946671690","https://openalex.org/W2946719178","https://openalex.org/W2955058313","https://openalex.org/W2962676885","https://openalex.org/W2963102968","https://openalex.org/W2963420686","https://openalex.org/W2963441822","https://openalex.org/W2963495494","https://openalex.org/W2963598138","https://openalex.org/W2963685207","https://openalex.org/W2963688992","https://openalex.org/W2963995996","https://openalex.org/W2964001806","https://openalex.org/W2964016027","https://openalex.org/W2964091467","https://openalex.org/W2964105113","https://openalex.org/W2969450957","https://openalex.org/W2970285700","https://openalex.org/W2972421866","https://openalex.org/W6679844565","https://openalex.org/W6746746423","https://openalex.org/W6753412334","https://openalex.org/W6760224987"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W4386925306","https://openalex.org/W4387968151","https://openalex.org/W3132124459","https://openalex.org/W2946083937","https://openalex.org/W2894986065","https://openalex.org/W4309346246"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,43,94,104,107,111,117,134,167,170],"task":[4],"of":[5,169],"3D":[6,161],"human":[7,76,162],"pose":[8,163],"estimation":[9,164],"from":[10],"a":[11,51,70,82,144],"single":[12],"RGB":[13],"image,":[14],"which":[15],"is":[16,57,79,91,114,122,149],"challenging":[17],"without":[18],"depth":[19],"information.":[20],"Recently":[21],"many":[22],"deep":[23],"learning":[24],"methods":[25,41],"are":[26,138],"proposed":[27,58,150,171],"and":[28,63,157],"achieve":[29],"great":[30],"improvements":[31],"due":[32],"to":[33,59,98,151],"their":[34],"strong":[35],"representation":[36],"learning.":[37],"However,":[38],"most":[39],"existing":[40],"ignore":[42],"relationship":[44,53,66,109],"between":[45,110],"joint":[46,52,65,127,132,136,145,154],"features.":[47,128],"In":[48],"this":[49],"paper,":[50],"aware":[54],"neural":[55,84],"network":[56],"take":[60],"both":[61],"global":[62,108],"local":[64,153],"into":[67,124],"consideration.":[68],"First,":[69],"whole":[71,95,112,119],"feature":[72,96,120],"block":[73,97,121],"representing":[74],"all":[75],"body":[77],"joints":[78,113],"extracted":[80],"by":[81,140],"convolutional":[83],"network.":[85],"A":[86],"Dual":[87],"Attention":[88],"Module":[89],"(DAM)":[90],"applied":[92],"on":[93,160],"generate":[99],"attention":[100,105],"weights.":[101],"By":[102],"exploiting":[103],"module,":[106],"encoded.":[115],"Second,":[116],"weighted":[118],"divided":[123],"some":[125],"individual":[126,135,141],"To":[129],"capture":[130],"salient":[131],"feature,":[133],"features":[137],"refined":[139],"DAMs.":[142],"Finally,":[143],"angle":[146],"prediction":[147],"constraint":[148],"consider":[152],"relationship.":[155],"Quantitative":[156],"qualitative":[158],"experiments":[159],"benchmarks":[165],"demonstrate":[166],"effectiveness":[168],"method.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2020-02-24T00:00:00"}
