{"id":"https://openalex.org/W2978362303","doi":"https://doi.org/10.1109/ijcnn.2019.8852263","title":"Context-Aware Network for 3D Human Pose Estimation from Monocular RGB Image","display_name":"Context-Aware Network for 3D Human Pose Estimation from Monocular RGB Image","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978362303","doi":"https://doi.org/10.1109/ijcnn.2019.8852263","mag":"2978362303"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5091558155","display_name":"Binyi Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binyi Yin","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657425","display_name":"Dongbo Zhang","orcid":"https://orcid.org/0000-0001-5076-340X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongbo Zhang","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424132","display_name":"Shuai Li","orcid":"https://orcid.org/0000-0003-4182-1588"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Li","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035153076","display_name":"Aimin Hao","orcid":"https://orcid.org/0000-0002-5774-6706"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aimin Hao","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091408797","display_name":"Hong Qin","orcid":"https://orcid.org/0000-0001-7699-1355"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Qin","raw_affiliation_strings":["Stony Brook University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"8"},"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":0.9970999956130981,"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":0.9945999979972839,"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/computer-science","display_name":"Computer science","score":0.8030081987380981},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7848995923995972},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7231565713882446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7125444412231445},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.660399317741394},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5875976085662842},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5551154017448425},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5346060991287231},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5118085741996765},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.46439793705940247},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.45405250787734985},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4110448360443115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36685019731521606},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3215777277946472},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07150518894195557},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05828458070755005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030081987380981},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7848995923995972},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7231565713882446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7125444412231445},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.660399317741394},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5875976085662842},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5551154017448425},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5346060991287231},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5118085741996765},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.46439793705940247},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.45405250787734985},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4110448360443115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36685019731521606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3215777277946472},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07150518894195557},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05828458070755005},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W2080873731","https://openalex.org/W2099471712","https://openalex.org/W2101032778","https://openalex.org/W2108598243","https://openalex.org/W2128271252","https://openalex.org/W2194775991","https://openalex.org/W2293220651","https://openalex.org/W2307770531","https://openalex.org/W2502928967","https://openalex.org/W2554247908","https://openalex.org/W2557698284","https://openalex.org/W2559085405","https://openalex.org/W2560023338","https://openalex.org/W2583372902","https://openalex.org/W2611932403","https://openalex.org/W2612706635","https://openalex.org/W2756050327","https://openalex.org/W2768477045","https://openalex.org/W2788865504","https://openalex.org/W2791697444","https://openalex.org/W2795089319","https://openalex.org/W2798646183","https://openalex.org/W2963402313","https://openalex.org/W2963446712","https://openalex.org/W2963516811","https://openalex.org/W2963688992","https://openalex.org/W2963781481","https://openalex.org/W2964016027","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W3098473649","https://openalex.org/W4320013936","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6696920397","https://openalex.org/W6697925102","https://openalex.org/W6704278359","https://openalex.org/W6730277886","https://openalex.org/W6746102887","https://openalex.org/W6746746423","https://openalex.org/W6785490181","https://openalex.org/W6966618176"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W200819717","https://openalex.org/W4387968151","https://openalex.org/W4386925306","https://openalex.org/W2032269556","https://openalex.org/W4307623796","https://openalex.org/W4394784820"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Network":[2,74],"(CNN)":[3],"has":[4],"brought":[5],"tremendous":[6],"improvements":[7],"in":[8,115],"estimating":[9,37],"3D":[10,22],"human":[11,23,41,47],"pose":[12,24,48],"from":[13,45],"a":[14,72],"monocular":[15],"RGB":[16],"image.":[17],"However,":[18],"the":[19,32,38,53,80,85],"task":[20,33],"of":[21,40,55,95],"estimation":[25,62],"still":[26],"remains":[27],"extremely":[28],"challenging,":[29],"especially":[30],"when":[31],"is":[34,98,113],"geared":[35],"towards":[36],"depth":[39,61],"body":[42,90],"parts.":[43,91],"Different":[44],"2D":[46],"estimation,":[49],"which":[50,76],"focuses":[51],"on":[52,138],"fusion":[54],"spatial":[56],"information":[57,82,108,121],"and":[58],"context":[59,65,81,107,120],"information,":[60],"demands":[63],"more":[64],"information.":[66],"Inspired":[67],"by":[68],"this,":[69],"we":[70],"build":[71],"Context-Aware":[73],"(CAN)":[75],"can":[77],"fully":[78],"explore":[79],"to":[83,105,118],"discover":[84],"underlying":[86],"relationships":[87],"among":[88],"different":[89,123],"The":[92],"key":[93],"ingredient":[94],"our":[96,116,129],"network":[97,117,130],"High-Level":[99],"Depth":[100],"Estimation":[101],"Module":[102],"(HLDEM)":[103],"designed":[104],"extract":[106,119],"effectively.":[109],"Additionally,":[110],"multi-scale":[111],"supervision":[112],"introduced":[114],"at":[122],"scales.":[124],"Experimental":[125],"results":[126],"show":[127],"that":[128],"achieves":[131],"competitive":[132],"performance":[133],"compared":[134],"with":[135],"state-of-the-art":[136],"methods":[137],"Human3.6M":[139],"dataset.":[140]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
