{"id":"https://openalex.org/W4403535119","doi":"https://doi.org/10.1109/icarm62033.2024.10715863","title":"DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network","display_name":"DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network","publication_year":2024,"publication_date":"2024-07-08","ids":{"openalex":"https://openalex.org/W4403535119","doi":"https://doi.org/10.1109/icarm62033.2024.10715863"},"language":"en","primary_location":{"id":"doi:10.1109/icarm62033.2024.10715863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm62033.2024.10715863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Advanced Robotics and Mechatronics (ICARM)","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/A5023146284","display_name":"Shaokun Zhang","orcid":"https://orcid.org/0000-0001-9542-0574"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaokun Zhang","raw_affiliation_strings":["Southeast University,School of Automation,Nanjing,China,210008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Automation,Nanjing,China,210008","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010863275","display_name":"Xinde Li","orcid":"https://orcid.org/0000-0002-1529-4537"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinde Li","raw_affiliation_strings":["Southeast University,School of Automation,Nanjing,China,210008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Automation,Nanjing,China,210008","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047723747","display_name":"Chuanfei Hu","orcid":"https://orcid.org/0000-0003-1669-9429"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanfei Hu","raw_affiliation_strings":["Southeast University,School of Automation,Nanjing,China,210008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southeast University,School of Automation,Nanjing,China,210008","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010683481","display_name":"Jianping Xu","orcid":"https://orcid.org/0000-0003-3427-1709"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Xu","raw_affiliation_strings":["Science and Technology on Information Systems Engineering Laboratory,Nanjing,China,21007"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory,Nanjing,China,21007","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041101317","display_name":"Huaping Liu","orcid":"https://orcid.org/0000-0002-4042-6044"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaping Liu","raw_affiliation_strings":["Tsinghua University,Department of Computer Science and Technology,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Computer Science and Technology,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"484","last_page":"489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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":0.9993000030517578,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6668148636817932},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5371914505958557},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5087247490882874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5059406161308289},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4832533001899719},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.45477646589279175},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4479776620864868},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37147191166877747},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1812625229358673},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1474933922290802},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0940592885017395},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.06182536482810974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668148636817932},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5371914505958557},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5087247490882874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5059406161308289},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4832533001899719},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.45477646589279175},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4479776620864868},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37147191166877747},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1812625229358673},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1474933922290802},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0940592885017395},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.06182536482810974},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm62033.2024.10715863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm62033.2024.10715863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2307770531","https://openalex.org/W2605648900","https://openalex.org/W2611932403","https://openalex.org/W2916798096","https://openalex.org/W2964221239","https://openalex.org/W3007690119","https://openalex.org/W3126541466","https://openalex.org/W3127541398","https://openalex.org/W3136525061","https://openalex.org/W3160306726","https://openalex.org/W3173811519","https://openalex.org/W3210908220","https://openalex.org/W4283021119","https://openalex.org/W4285175808","https://openalex.org/W4310374351","https://openalex.org/W4312249545","https://openalex.org/W4312417903","https://openalex.org/W4312925317","https://openalex.org/W4313161900","https://openalex.org/W4366147955","https://openalex.org/W4379985979","https://openalex.org/W4385245566","https://openalex.org/W4385767582","https://openalex.org/W4386076485","https://openalex.org/W4386083126","https://openalex.org/W4390873166","https://openalex.org/W4394597906","https://openalex.org/W6726873649","https://openalex.org/W6849449126"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W4387968151","https://openalex.org/W4386925306","https://openalex.org/W3132124459","https://openalex.org/W2946083937","https://openalex.org/W2894986065","https://openalex.org/W4299867837","https://openalex.org/W3110557940"],"abstract_inverted_index":{"Recent":[0],"transformer-based":[1],"methods":[2,16],"for":[3],"estimating":[4],"3D":[5],"human":[6,26,54,89],"pose":[7],"have":[8,17],"gained":[9],"widespread":[10],"attention,":[11],"achieving":[12],"state-of-the-art":[13,142],"results.":[14],"Previous":[15],"primarily":[18],"focused":[19],"on":[20,128],"capturing":[21],"motion":[22,50,63,86],"patterns":[23,51,87],"of":[24,52,88,113,157],"the":[25,53,61,81,111,129,150],"body":[27,55],"at":[28,56],"a":[29,96],"single":[30],"scale":[31],"or":[32,122],"cascading":[33],"multiple":[34],"scales,":[35],"such":[36],"as":[37],"joints,":[38],"bones,":[39],"and":[40,73,84,91,116,133,160],"body-parts.":[41],"However,":[42],"they":[43],"are":[44,126,136],"difficult":[45],"to":[46,60,109,140],"simultaneously":[47],"capture":[48],"spatial-temporal":[49],"different":[57],"scales":[58],"due":[59],"complex":[62],"patterns.":[64],"To":[65],"address":[66],"this":[67],"issue,":[68],"we":[69,94],"propose":[70],"Dual-scale":[71],"Spatial":[72],"Temporal":[74],"transFormer":[75],"(DSTFormer),":[76],"which":[77,101],"can":[78],"concurrently":[79],"explore":[80],"spatial":[82],"dependencies":[83],"temporal":[85],"joints":[90,121],"bones.":[92,123],"Additionally,":[93],"introduce":[95],"Gcn-Spatial":[97],"Transformer":[98],"Block":[99],"(GSTB),":[100],"introduces":[102],"Graph":[103],"Convolutional":[104],"Networks":[105],"(GCN)":[106],"into":[107],"transformer":[108],"enhance":[110],"exploitation":[112],"local":[114],"relationships":[115],"global":[117],"information":[118],"between":[119],"adjacent":[120],"Extensive":[124],"experiments":[125],"conducted":[127],"Human3.6M":[130],"benchmark":[131],"dataset,":[132],"superior":[134],"results":[135],"reported":[137],"when":[138],"comparing":[139],"other":[141],"methods.":[143],"More":[144],"remarkably,":[145],"our":[146],"model":[147],"achieves":[148],"to-date":[149],"best":[151],"published":[152],"performance,":[153],"with":[154],"P1":[155],"errors":[156],"37.9":[158],"mm":[159],"15.6":[161],"mm,":[162],"respectively.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
