{"id":"https://openalex.org/W4367316837","doi":"https://doi.org/10.3390/e25050724","title":"Repeated Cross-Scale Structure-Induced Feature Fusion Network for 2D Hand Pose Estimation","display_name":"Repeated Cross-Scale Structure-Induced Feature Fusion Network for 2D Hand Pose Estimation","publication_year":2023,"publication_date":"2023-04-27","ids":{"openalex":"https://openalex.org/W4367316837","doi":"https://doi.org/10.3390/e25050724","pmid":"https://pubmed.ncbi.nlm.nih.gov/37238479"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25050724","pdf_url":"https://www.mdpi.com/1099-4300/25/5/724/pdf?version=1682586762","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"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},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/25/5/724/pdf?version=1682586762","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101956285","display_name":"Xin Guan","orcid":"https://orcid.org/0000-0003-4501-0483"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Guan","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102113612","display_name":"Huan Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Shen","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073614359","display_name":"Charles Okanda Nyatega","orcid":"https://orcid.org/0000-0003-1783-7811"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Charles Okanda Nyatega","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100429894","display_name":"Qiang Li","orcid":"https://orcid.org/0000-0001-7129-1456"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Li","raw_affiliation_strings":["School of Microelectronics, Tianjin University, Tianjin 300072, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University, Tianjin 300072, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5073614359","https://openalex.org/A5100429894"],"corresponding_institution_ids":["https://openalex.org/I162868743","https://openalex.org/I162868743"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165,"provenance":"doaj"},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165,"provenance":"doaj"},"fwci":0.325,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":1,"citation_normalized_percentile":{"value":0.588886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":69,"max":80},"biblio":{"volume":"25","issue":"5","first_page":"724","last_page":"724"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Action Recognition and Pose Estimation","score":0.9997,"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 Action Recognition and Pose Estimation","score":0.9997,"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/T11398","display_name":"Gesture Recognition in Human-Computer Interaction","score":0.9953,"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/T10653","display_name":"Robotic Grasping and Learning from Demonstration","score":0.9735,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6878911},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6850872},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture Recognition","score":0.566389},{"id":"https://openalex.org/keywords/object-pose-estimation","display_name":"Object Pose Estimation","score":0.547198},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.54280055},{"id":"https://openalex.org/keywords/pose-estimation","display_name":"Pose Estimation","score":0.537154},{"id":"https://openalex.org/keywords/continuous-recognition","display_name":"Continuous Recognition","score":0.536343},{"id":"https://openalex.org/keywords/3d-object-recognition","display_name":"3D Object Recognition","score":0.5316},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48128623},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4517391}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.76267344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7433032},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6878911},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6850872},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6264875},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6085729},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6016525},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.57401025},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.54280055},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48128623},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4614699},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4517391},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35510698},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14670706},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25050724","pdf_url":"https://www.mdpi.com/1099-4300/25/5/724/pdf?version=1682586762","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"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},{"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216948","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37238479","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25050724","pdf_url":"https://www.mdpi.com/1099-4300/25/5/724/pdf?version=1682586762","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"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},"sustainable_development_goals":[{"score":0.4,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"grants":[{"funder":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City","award_id":"16JCZDJC31100"}],"datasets":[],"versions":[],"referenced_works_count":35,"referenced_works":["https://openalex.org/W1928739709","https://openalex.org/W1943054406","https://openalex.org/W2075156252","https://openalex.org/W2215643317","https://openalex.org/W2466332079","https://openalex.org/W2501902603","https://openalex.org/W2565639579","https://openalex.org/W2583491955","https://openalex.org/W2774831247","https://openalex.org/W2897765997","https://openalex.org/W2900273708","https://openalex.org/W2913308533","https://openalex.org/W2916798096","https://openalex.org/W2962811204","https://openalex.org/W2963119249","https://openalex.org/W2963488642","https://openalex.org/W2964093990","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W2979577579","https://openalex.org/W2989674076","https://openalex.org/W3009765082","https://openalex.org/W3010448990","https://openalex.org/W3011857662","https://openalex.org/W3013785695","https://openalex.org/W3080830001","https://openalex.org/W3105217837","https://openalex.org/W3202568410","https://openalex.org/W4213170480","https://openalex.org/W4220880481","https://openalex.org/W4233655449","https://openalex.org/W4237718774","https://openalex.org/W4294872070","https://openalex.org/W4313525357","https://openalex.org/W4320496440"],"related_works":["https://openalex.org/W4386085515","https://openalex.org/W4200151779","https://openalex.org/W3102636071","https://openalex.org/W2997897143","https://openalex.org/W2972219788","https://openalex.org/W2956571887","https://openalex.org/W2954208830","https://openalex.org/W2900273708","https://openalex.org/W2822883015","https://openalex.org/W2295870746"],"abstract_inverted_index":{"Recently,":[0],"the":[1,50,73,82,153,162,172],"use":[2,156],"of":[3,75,88,93],"convolutional":[4],"neural":[5],"networks":[6],"for":[7,175],"hand":[8,22,102,144,177],"pose":[9,23,178],"estimation":[10,24,179],"from":[11,41],"RGB":[12],"images":[13],"has":[14],"dramatically":[15],"improved.":[16],"However,":[17],"self-occluded":[18],"keypoint":[19,125],"inference":[20],"in":[21],"is":[25,52],"still":[26],"a":[27,62,106,129],"challenging":[28],"task.":[29],"We":[30],"argue":[31],"that":[32,148,168],"these":[33],"occluded":[34,151],"keypoints":[35,51,76],"cannot":[36],"be":[37],"readily":[38],"recognized":[39],"directly":[40],"traditional":[42],"appearance":[43,138],"features,":[44],"and":[45,97,116,185],"sufficient":[46],"contextual":[47],"information":[48,115],"among":[49],"especially":[53],"needed":[54],"to":[55,70,159],"induce":[56],"feature":[57,67,108,132],"learning.":[58],"Therefore,":[59],"we":[60],"propose":[61],"new":[63,107],"repeated":[64],"cross-scale":[65,131],"structure-induced":[66],"fusion":[68,133],"network":[69,91,154],"learn":[71],"about":[72],"representations":[74],"with":[77],"rich":[78],"information,":[79,146],"'informed'":[80],"by":[81,111,141],"relationships":[83],"between":[84],"different":[85],"abstraction":[86],"levels":[87],"features.":[89],"Our":[90],"consists":[92],"two":[94,181],"modules:":[95],"GlobalNet":[96,99],"RegionalNet.":[98],"roughly":[100],"locates":[101],"joints":[103],"based":[104],"on":[105,180],"pyramid":[109],"structure":[110,145],"combining":[112],"higher":[113],"semantic":[114],"more":[117,142],"global":[118],"spatial":[119],"scale":[120],"information.":[121],"RegionalNet":[122],"further":[123],"refines":[124],"representation":[126],"learning":[127],"via":[128],"four-stage":[130],"network,":[134],"which":[135],"learns":[136],"shallow":[137],"features":[139,158],"induced":[140],"implicit":[143],"so":[147],"when":[149],"identifying":[150],"keypoints,":[152],"can":[155],"augmented":[157],"better":[160],"locate":[161],"positions.":[163],"The":[164],"experimental":[165],"results":[166],"show":[167],"our":[169],"method":[170],"outperforms":[171],"state-of-the-art":[173],"methods":[174],"2D":[176],"public":[182],"datasets,":[183],"STB":[184],"RHD.":[186]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4367316837","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2024-11-19T16:21:18.494551","created_date":"2023-04-29"}
