{"id":"https://openalex.org/W3039581541","doi":"https://doi.org/10.3390/sym12071116","title":"Multi-View Pose Generator Based on Deep Learning for Monocular 3D Human Pose Estimation","display_name":"Multi-View Pose Generator Based on Deep Learning for Monocular 3D Human Pose Estimation","publication_year":2020,"publication_date":"2020-07-04","ids":{"openalex":"https://openalex.org/W3039581541","doi":"https://doi.org/10.3390/sym12071116","mag":"3039581541"},"language":"en","primary_location":{"id":"doi:10.3390/sym12071116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12071116","pdf_url":"https://www.mdpi.com/2073-8994/12/7/1116/pdf?version=1594824185","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/12/7/1116/pdf?version=1594824185","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100429004","display_name":"Jun Sun","orcid":"https://orcid.org/0000-0002-3545-1392"},"institutions":[{"id":"https://openalex.org/I37574244","display_name":"Sichuan Agricultural University","ror":"https://ror.org/0388c3403","country_code":"CN","type":"education","lineage":["https://openalex.org/I37574244"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Sun","raw_affiliation_strings":["College of Information and Engineering, Sichuan Agricultural University, Yaan 625014, China","The Lab of Agricultural Information Engineering, Sichuan Key Laboratory, Yaan 625014, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Engineering, Sichuan Agricultural University, Yaan 625014, China","institution_ids":["https://openalex.org/I37574244"]},{"raw_affiliation_string":"The Lab of Agricultural Information Engineering, Sichuan Key Laboratory, Yaan 625014, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087437830","display_name":"Mantao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I37574244","display_name":"Sichuan Agricultural University","ror":"https://ror.org/0388c3403","country_code":"CN","type":"education","lineage":["https://openalex.org/I37574244"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mantao Wang","raw_affiliation_strings":["College of Information and Engineering, Sichuan Agricultural University, Yaan 625014, China","The Lab of Agricultural Information Engineering, Sichuan Key Laboratory, Yaan 625014, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Engineering, Sichuan Agricultural University, Yaan 625014, China","institution_ids":["https://openalex.org/I37574244"]},{"raw_affiliation_string":"The Lab of Agricultural Information Engineering, Sichuan Key Laboratory, Yaan 625014, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668752","display_name":"Xin Zhao","orcid":"https://orcid.org/0000-0003-2176-7537"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhao","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064727229","display_name":"Dejun Zhang","orcid":"https://orcid.org/0000-0001-9129-534X"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dejun Zhang","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"],"raw_orcid":"https://orcid.org/0000-0001-9129-534X","affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087437830"],"corresponding_institution_ids":["https://openalex.org/I37574244"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.8661,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.72844138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"12","issue":"7","first_page":"1116","last_page":"1116"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962999820709229,"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":0.9937000274658203,"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/pose","display_name":"Pose","score":0.9345117807388306},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.8212556838989258},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8056504130363464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7699792385101318},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.7461930513381958},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.643496036529541},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5534725189208984},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.546875},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5157768726348877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3682401776313782},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35104119777679443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.06529173254966736}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.9345117807388306},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.8212556838989258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8056504130363464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7699792385101318},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.7461930513381958},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.643496036529541},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5534725189208984},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.546875},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5157768726348877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3682401776313782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35104119777679443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.06529173254966736},{"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},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym12071116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12071116","pdf_url":"https://www.mdpi.com/2073-8994/12/7/1116/pdf?version=1594824185","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a47d7f96404d41af8afde850a6c00563","is_oa":true,"landing_page_url":"https://doaj.org/article/a47d7f96404d41af8afde850a6c00563","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 12, Iss 7, p 1116 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/12/7/1116/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym12071116","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym12071116","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12071116","pdf_url":"https://www.mdpi.com/2073-8994/12/7/1116/pdf?version=1594824185","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8017026071","display_name":null,"funder_award_id":"61702350","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3039581541.pdf","grobid_xml":"https://content.openalex.org/works/W3039581541.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W976039271","https://openalex.org/W1665214252","https://openalex.org/W1987354253","https://openalex.org/W2066562487","https://openalex.org/W2099471712","https://openalex.org/W2101032778","https://openalex.org/W2188365844","https://openalex.org/W2519887557","https://openalex.org/W2526044239","https://openalex.org/W2604375920","https://openalex.org/W2612163384","https://openalex.org/W2612706635","https://openalex.org/W2754534665","https://openalex.org/W2756050327","https://openalex.org/W2765721570","https://openalex.org/W2765789968","https://openalex.org/W2784435047","https://openalex.org/W2795089319","https://openalex.org/W2803773316","https://openalex.org/W2886552305","https://openalex.org/W2909461549","https://openalex.org/W2940457086","https://openalex.org/W2945071622","https://openalex.org/W2950977907","https://openalex.org/W2952270885","https://openalex.org/W2953258117","https://openalex.org/W2953333925","https://openalex.org/W2963076818","https://openalex.org/W2963091558","https://openalex.org/W2963102968","https://openalex.org/W2963441822","https://openalex.org/W2963772981","https://openalex.org/W2964016027","https://openalex.org/W2964179555","https://openalex.org/W2964318832","https://openalex.org/W2966735886","https://openalex.org/W2969676305","https://openalex.org/W2971476609","https://openalex.org/W2972662547","https://openalex.org/W2981660954","https://openalex.org/W3008567450","https://openalex.org/W3008631374","https://openalex.org/W3010350980","https://openalex.org/W3011709144","https://openalex.org/W3013477486","https://openalex.org/W3014899985","https://openalex.org/W3035419359","https://openalex.org/W3098612954","https://openalex.org/W3205717647","https://openalex.org/W6727822593","https://openalex.org/W6744234597","https://openalex.org/W6758209225","https://openalex.org/W6762635240","https://openalex.org/W6766577339"],"related_works":["https://openalex.org/W2113785214","https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W4299867837","https://openalex.org/W4386075737","https://openalex.org/W2951583186","https://openalex.org/W1974260915","https://openalex.org/W4382141741","https://openalex.org/W2088028039","https://openalex.org/W3165753266"],"abstract_inverted_index":{"In":[0],"this":[1,46],"paper,":[2],"we":[3,68,84,104,141],"study":[4],"the":[5,22,29,37,65,96,122,161,165,171,179],"problem":[6],"of":[7,121,133,167,181],"monocular":[8,23,78],"3D":[9,40,73,79,149,183],"human":[10,24,80],"pose":[11,25,41,74,81,88,117,135,150,184],"estimation":[12,26,42,75,185],"based":[13,39],"on":[14,119,158],"deep":[15],"learning.":[16],"Due":[17],"to":[18,44,90,146],"single":[19,101],"view":[20],"limitations,":[21],"cannot":[27,51],"avoid":[28],"inherent":[30],"occlusion":[31],"problem.":[32,47],"The":[33],"common":[34],"methods":[35],"use":[36],"multi-view":[38,56,87,92,115,152],"method":[43,112,177],"solve":[45],"However,":[48],"single-view":[49],"images":[50],"be":[52],"used":[53],"directly":[54],"in":[55,99,137],"methods,":[57],"which":[58],"greatly":[59],"limits":[60],"practical":[61],"applications.":[62],"To":[63],"address":[64],"above-mentioned":[66],"issues,":[67],"propose":[69,85,105],"a":[70,86,100,106,130,148],"novel":[71],"end-to-end":[72],"network":[76,145],"for":[77,113],"estimation.":[82],"First,":[83],"generator":[89],"predict":[91],"2D":[93,97,116,134,153],"poses":[94,98],"from":[95,151],"view.":[102],"Secondly,":[103],"simple":[107],"but":[108],"effective":[109],"data":[110],"augmentation":[111],"generating":[114],"annotations,":[118],"account":[120],"existing":[123,182],"datasets":[124],"(e.g.,":[125],"Human3.6M,":[126],"etc.)":[127],"not":[128],"containing":[129],"large":[131],"number":[132],"annotations":[136],"different":[138],"views.":[139],"Thirdly,":[140],"employ":[142],"graph":[143],"convolutional":[144],"infer":[147],"poses.":[154],"From":[155],"experiments":[156],"conducted":[157],"public":[159],"datasets,":[160],"results":[162],"have":[163],"verified":[164],"effectiveness":[166],"our":[168,176],"method.":[169],"Furthermore,":[170],"ablation":[172],"studies":[173],"show":[174],"that":[175],"improved":[178],"performance":[180],"networks.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
