{"id":"https://openalex.org/W4385286377","doi":"https://doi.org/10.1109/lsp.2023.3299209","title":"Depth-Hand: 3D Hand Keypoint Detection With Dense Depth Estimation","display_name":"Depth-Hand: 3D Hand Keypoint Detection With Dense Depth Estimation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385286377","doi":"https://doi.org/10.1109/lsp.2023.3299209"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2023.3299209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3299209","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-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/A5081451717","display_name":"Shuqiao Sun","orcid":"https://orcid.org/0000-0002-5420-9745"},"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":true,"raw_author_name":"Shuqiao Sun","raw_affiliation_strings":["Department of Electronic Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077936056","display_name":"Rongke Liu","orcid":"https://orcid.org/0000-0003-3098-8649"},"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":"Rongke Liu","raw_affiliation_strings":["Department of Electronic Information Engineering, Beihang University, Beijing, China","Shenzhen Institution, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Shenzhen Institution, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100719715","display_name":"Xin Yang","orcid":"https://orcid.org/0000-0003-3428-3806"},"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":"Xinxin Yang","raw_affiliation_strings":["Department of Electronic Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081451717"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.5174,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65742263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"30","issue":null,"first_page":"962","last_page":"966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.805881142616272},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7356876134872437},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.5811032056808472},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5651949048042297},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.55504310131073},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5355439186096191},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.521273136138916},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.47020986676216125},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4694000780582428},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44290661811828613},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29679417610168457},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09824973344802856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.805881142616272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7356876134872437},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.5811032056808472},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5651949048042297},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.55504310131073},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5355439186096191},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.521273136138916},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.47020986676216125},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4694000780582428},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44290661811828613},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29679417610168457},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09824973344802856},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2023.3299209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3299209","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.4399999976158142,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2218414108","https://openalex.org/W2259424905","https://openalex.org/W2606627193","https://openalex.org/W2606965392","https://openalex.org/W2609674290","https://openalex.org/W2612445135","https://openalex.org/W2774831247","https://openalex.org/W2963163009","https://openalex.org/W2963508807","https://openalex.org/W2970455351","https://openalex.org/W2972487609","https://openalex.org/W2998383791","https://openalex.org/W3004166074","https://openalex.org/W3009175371","https://openalex.org/W3015865682","https://openalex.org/W3021761487","https://openalex.org/W3034514115","https://openalex.org/W3047965053","https://openalex.org/W3106042222","https://openalex.org/W3112869574","https://openalex.org/W3113017205","https://openalex.org/W3158805747","https://openalex.org/W3180029730","https://openalex.org/W3197994121","https://openalex.org/W4200186532","https://openalex.org/W4226367687","https://openalex.org/W4281924584","https://openalex.org/W4285428280","https://openalex.org/W4296545380","https://openalex.org/W4297775537","https://openalex.org/W4307156142","https://openalex.org/W4312951879","https://openalex.org/W4319990484","https://openalex.org/W4385632207"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W2368824897","https://openalex.org/W1508050556","https://openalex.org/W1910862367","https://openalex.org/W2379365082","https://openalex.org/W2370747590","https://openalex.org/W2030109976","https://openalex.org/W2369260257","https://openalex.org/W2389120450","https://openalex.org/W55249799"],"abstract_inverted_index":{"Hand":[0],"pose":[1],"is":[2,10,80,98,116,130,146,163],"important":[3],"to":[4,106,149],"various":[5],"applications":[6],"and":[7,34,73,86,136],"depth":[8,26,57,71,103,134,168],"information":[9],"crucial":[11],"for":[12],"a":[13,38,45,107,111,124,143],"reliable":[14],"3D":[15,51,137,173],"keypoint":[16,75],"detection.":[17],"However,":[18],"scopes":[19],"of":[20,69,109,165],"methods":[21],"that":[22,48,159],"rely":[23],"on":[24,64],"active":[25],"cameras":[27],"are":[28],"limited":[29],"by":[30],"the":[31,65,70,77,95,102,119,151,152,160],"power,":[32],"volume":[33],"illumination.":[35],"To":[36,90],"explore":[37],"wider":[39],"application":[40],"range,":[41],"this":[42],"letter":[43],"proposes":[44],"multi-task":[46],"method":[47,129,162],"can":[49],"detect":[50],"hand":[52,74,96,138,174],"keypoints":[53,139],"while":[54],"estimating":[55],"dense":[56],"maps":[58,169],"from":[59,101],"stereo":[60,133],"infrared":[61],"inputs.":[62],"Based":[63],"inherent":[66],"encoding-decoding":[67],"relation":[68],"estimation":[72],"detection,":[76],"proposed":[78,128,161],"network":[79],"built":[81,148],"with":[82,123,171],"shared":[83],"intermediate":[84],"features":[85],"separate":[87],"task":[88],"branches.":[89],"achieve":[91],"an":[92],"end-to-end":[93],"estimation,":[94],"region":[97],"automatically":[99],"cropped":[100],"map.":[104],"Due":[105],"lack":[108],"datasets,":[110],"two-step":[112],"fusion":[113],"training":[114],"approach":[115],"designed":[117],"following":[118],"transfer":[120],"learning":[121],"theory":[122],"self-supervision":[125],"loss.":[126],"The":[127],"evaluated":[131],"under":[132],"datasets":[135,140],"respectively.":[141],"Meanwhile,":[142],"small":[144],"dataset":[145],"also":[147],"test":[150],"overall":[153],"model":[154],"performance.":[155],"Experimental":[156],"results":[157],"prove":[158],"capable":[164],"providing":[166],"satisfying":[167],"along":[170],"convincing":[172],"keypoints.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}