{"id":"https://openalex.org/W4390873007","doi":"https://doi.org/10.1109/iccv51070.2023.01348","title":"Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images","display_name":"Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390873007","doi":"https://doi.org/10.1109/iccv51070.2023.01348"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01348","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2308.11015","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017172598","display_name":"Tze Ho Elden Tse","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"funder","lineage":["https://openalex.org/I79619799"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Tze Ho Elden Tse","raw_affiliation_strings":["Google","University of Birmingham"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"University of Birmingham","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072277461","display_name":"Franziska Mueller","orcid":"https://orcid.org/0000-0003-2036-9238"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Franziska Mueller","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102848878","display_name":"Zhengyang Shen","orcid":"https://orcid.org/0000-0003-3442-6344"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengyang Shen","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052922425","display_name":"Danhang Tang","orcid":"https://orcid.org/0000-0001-6164-8263"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danhang Tang","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013075810","display_name":"Thabo Beeler","orcid":"https://orcid.org/0000-0002-8077-1205"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thabo Beeler","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056997314","display_name":"Mingsong Dou","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingsong Dou","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058136382","display_name":"Yinda Zhang","orcid":"https://orcid.org/0000-0001-5386-8872"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yinda Zhang","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109325841","display_name":"Sa\u0161a Petrovi\u0107","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sasa Petrovic","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004895698","display_name":"Hyung Jin Chang","orcid":"https://orcid.org/0000-0001-7495-9677"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"funder","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hyung Jin Chang","raw_affiliation_strings":["University of Birmingham"],"affiliations":[{"raw_affiliation_string":"University of Birmingham","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039055363","display_name":"Jonathan M. Taylor","orcid":"https://orcid.org/0000-0001-7047-1789"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Taylor","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005391091","display_name":"Bardia Doosti","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"funder","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bardia Doosti","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":67},"biblio":{"volume":null,"issue":null,"first_page":"14620","last_page":"14631"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9924,"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":0.9924,"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":0.9736,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6222964},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5741607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80261254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.74492383},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6222964},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5776101},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5741607},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5189414},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4229594},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.41457224},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22720316},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.100203425}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01348","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2308.11015","pdf_url":"https://arxiv.org/pdf/2308.11015","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2308.11015","pdf_url":"https://arxiv.org/pdf/2308.11015","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":64,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1590889181","https://openalex.org/W1836465849","https://openalex.org/W2117539524","https://openalex.org/W2135957668","https://openalex.org/W2150457612","https://openalex.org/W2175031088","https://openalex.org/W2194775991","https://openalex.org/W2227547437","https://openalex.org/W2605973302","https://openalex.org/W2768683308","https://openalex.org/W2948343307","https://openalex.org/W2955425717","https://openalex.org/W2962849139","https://openalex.org/W2963926543","https://openalex.org/W2964093990","https://openalex.org/W2964211001","https://openalex.org/W2964321699","https://openalex.org/W2968722025","https://openalex.org/W2973857456","https://openalex.org/W2979577579","https://openalex.org/W2984313141","https://openalex.org/W2990081853","https://openalex.org/W3034395814","https://openalex.org/W3034470433","https://openalex.org/W3034971010","https://openalex.org/W3035068106","https://openalex.org/W3035385851","https://openalex.org/W3035581100","https://openalex.org/W3048921023","https://openalex.org/W3094927600","https://openalex.org/W3107167007","https://openalex.org/W3107290753","https://openalex.org/W3107384982","https://openalex.org/W3107825842","https://openalex.org/W3108094035","https://openalex.org/W3109877674","https://openalex.org/W3173636439","https://openalex.org/W3175199633","https://openalex.org/W3177075049","https://openalex.org/W3199621649","https://openalex.org/W3201806127","https://openalex.org/W3202237431","https://openalex.org/W3202568410","https://openalex.org/W3215769467","https://openalex.org/W4206706211","https://openalex.org/W4214684804","https://openalex.org/W4221151978","https://openalex.org/W4226318466","https://openalex.org/W4226524636","https://openalex.org/W4230962939","https://openalex.org/W4251395003","https://openalex.org/W4285102579","https://openalex.org/W4287123803","https://openalex.org/W4287829537","https://openalex.org/W4298014233","https://openalex.org/W4308014920","https://openalex.org/W4312275452","https://openalex.org/W4312310174","https://openalex.org/W4312595848","https://openalex.org/W4312597750","https://openalex.org/W4385245566","https://openalex.org/W4386076518","https://openalex.org/W4390874241"],"related_works":["https://openalex.org/W4385574037","https://openalex.org/W4310746709","https://openalex.org/W3155117723","https://openalex.org/W2607795551","https://openalex.org/W2366350639","https://openalex.org/W2281134365","https://openalex.org/W2062399876","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W1557607869"],"abstract_inverted_index":{"We":[0],"propose":[1,111],"a":[2,26,40,79,88,115],"novel":[3],"transformer-based":[4],"framework":[5,148],"that":[6,146],"reconstructs":[7],"two":[8,112],"high":[9,59],"fidelity":[10],"hands":[11],"from":[12,34,61,91],"multi-view":[13,99],"RGB":[14,36],"images.":[15],"Unlike":[16],"existing":[17,65],"hand":[18,31],"pose":[19],"estimation":[20],"methods,":[21],"where":[22,45],"one":[23],"typically":[24],"trains":[25],"deep":[27],"network":[28],"to":[29,95,121,135,151,163],"regress":[30,48],"model":[32],"parameters":[33],"single":[35],"image,":[37],"we":[38,46,77,110,144],"consider":[39],"more":[41],"challenging":[42],"problem":[43],"setting":[44],"directly":[47],"the":[49,106,123,158],"absolute":[50],"root":[51],"poses":[52],"of":[53,160],"two-hands":[54],"with":[55,83],"extended":[56],"forearm":[57],"at":[58,133],"resolution":[60],"egocentric":[62,71],"view.":[63],"As":[64],"datasets":[66],"are":[67],"either":[68],"infeasible":[69],"for":[70],"viewpoints":[72],"or":[73],"lack":[74],"background":[75],"variations,":[76],"create":[78],"large-scale":[80],"synthetic":[81],"dataset":[82,90],"diverse":[84],"scenarios":[85],"and":[86,127,141,156],"collect":[87],"real":[89,164],"multi-calibrated":[92],"camera":[93],"setup":[94],"verify":[96],"our":[97,147],"proposed":[98],"image":[100],"feature":[101],"fusion":[102],"strategy.":[103],"To":[104],"make":[105],"reconstruction":[107],"physically":[108],"plausible,":[109],"strategies:":[113],"(i)":[114],"coarse-to-fine":[116],"spectral":[117],"graph":[118],"convolution":[119],"decoder":[120],"smoothen":[122],"meshes":[124],"during":[125],"upsampling":[126],"(ii)":[128],"an":[129],"optimisation-based":[130],"refinement":[131],"stage":[132],"inference":[134],"prevent":[136],"self-penetrations.":[137],"Through":[138],"extensive":[139],"quantitative":[140],"qualitative":[142],"evaluations,":[143],"show":[145],"is":[149],"able":[150],"produce":[152],"realistic":[153],"two-hand":[154],"reconstructions":[155],"demonstrate":[157],"generalisation":[159],"synthetic-trained":[161],"models":[162],"data,":[165],"as":[166,168],"well":[167],"real-time":[169],"AR/VR":[170],"applications.":[171]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4390873007","counts_by_year":[],"updated_date":"2025-01-28T06:20:19.067703","created_date":"2024-01-16"}