{"id":"https://openalex.org/W3034798648","doi":"https://doi.org/10.1109/cvpr42600.2020.00068","title":"FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction","display_name":"FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3034798648","doi":"https://doi.org/10.1109/cvpr42600.2020.00068","mag":"3034798648"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00068","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/2003.13989","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039635960","display_name":"Haotian Yang","orcid":"https://orcid.org/0000-0002-2682-1806"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Yang","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043239430","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0003-1596-4366"},"institutions":[{"id":"https://openalex.org/I4210129579","display_name":"National Engineering Laboratory of Deep Learning Technology and Application","ror":"https://ror.org/03z8p5796","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129579"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"funder","lineage":["https://openalex.org/I98301712"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["Baidu Research","Nanjing University","National Engineering Laboratory for Deep Learning Technology and Applications, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Deep Learning Technology and Applications, China","institution_ids":["https://openalex.org/I4210129579"]},{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115695494","display_name":"Yanru Wang","orcid":"https://orcid.org/0000-0002-3244-7806"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanru Wang","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059850621","display_name":"Mingkai Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingkai Huang","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610821","display_name":"Qiu Shen","orcid":"https://orcid.org/0000-0001-5515-3125"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiu Shen","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076524203","display_name":"Ruigang Yang","orcid":"https://orcid.org/0000-0001-5296-6307"},"institutions":[{"id":"https://openalex.org/I4210129579","display_name":"National Engineering Laboratory of Deep Learning Technology and Application","ror":"https://ror.org/03z8p5796","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129579"]},{"id":"https://openalex.org/I4210158001","display_name":"Incept (United States)","ror":"https://ror.org/05fj65g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210158001"]},{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"funder","lineage":["https://openalex.org/I143302722"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"funder","lineage":["https://openalex.org/I98301712"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Ruigang Yang","raw_affiliation_strings":["Baidu Research","Inceptio Inc.","National Engineering Laboratory for Deep Learning Technology and Applications, China","University of Kentucky"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Deep Learning Technology and Applications, China","institution_ids":["https://openalex.org/I4210129579"]},{"raw_affiliation_string":"Inceptio Inc.","institution_ids":["https://openalex.org/I4210158001"]},{"raw_affiliation_string":"University of Kentucky","institution_ids":["https://openalex.org/I143302722"]},{"raw_affiliation_string":"Baidu Research","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058572381","display_name":"Xun Cao","orcid":"https://orcid.org/0000-0003-3094-4371"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"funder","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xun Cao","raw_affiliation_strings":["Nanjing University"],"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.65,"has_fulltext":false,"cited_by_count":237,"citation_normalized_percentile":{"value":0.999865,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"598","last_page":"607"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"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/T11448","display_name":"Face recognition and analysis","score":1.0,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9949,"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/T10057","display_name":"Face and Expression Recognition","score":0.9947,"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/code","display_name":"Code (set theory)","score":0.539232},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.49071085},{"id":"https://openalex.org/keywords/3d-model","display_name":"3d model","score":0.48894492},{"id":"https://openalex.org/keywords/displacement-mapping","display_name":"Displacement mapping","score":0.48485908}],"concepts":[{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.78655946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73498493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6769662},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.60553074},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.539232},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.51420426},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.50799376},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.49071085},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.48894492},{"id":"https://openalex.org/C123149101","wikidata":"https://www.wikidata.org/wiki/Q1229184","display_name":"Displacement mapping","level":3,"score":0.48485908},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45011672},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4360338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42514253},{"id":"https://openalex.org/C200585589","wikidata":"https://www.wikidata.org/wiki/Q752176","display_name":"Texture mapping","level":2,"score":0.13066399},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.09138408},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr42600.2020.00068","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/2003.13989","pdf_url":"https://arxiv.org/pdf/2003.13989","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/2003.13989","pdf_url":"https://arxiv.org/pdf/2003.13989","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":63,"referenced_works":["https://openalex.org/W1566413196","https://openalex.org/W1776042733","https://openalex.org/W1814840193","https://openalex.org/W1973757125","https://openalex.org/W1976295221","https://openalex.org/W1992187125","https://openalex.org/W2012048984","https://openalex.org/W2012075579","https://openalex.org/W2017107803","https://openalex.org/W2030616426","https://openalex.org/W2038891881","https://openalex.org/W2051297709","https://openalex.org/W2086331119","https://openalex.org/W2107037917","https://openalex.org/W2114795754","https://openalex.org/W2135666716","https://openalex.org/W2137306662","https://openalex.org/W2137659841","https://openalex.org/W2155211928","https://openalex.org/W2160014001","https://openalex.org/W2163131540","https://openalex.org/W2168722300","https://openalex.org/W2237250383","https://openalex.org/W2265959009","https://openalex.org/W2301937176","https://openalex.org/W2310705318","https://openalex.org/W2431101926","https://openalex.org/W2486034530","https://openalex.org/W2501306710","https://openalex.org/W2525547705","https://openalex.org/W2542323081","https://openalex.org/W2555510177","https://openalex.org/W2582523095","https://openalex.org/W2593414223","https://openalex.org/W2604524889","https://openalex.org/W2605701576","https://openalex.org/W2769666294","https://openalex.org/W2771328060","https://openalex.org/W2775877962","https://openalex.org/W2795709097","https://openalex.org/W2796822548","https://openalex.org/W2798409702","https://openalex.org/W2799116135","https://openalex.org/W2799185473","https://openalex.org/W2803705807","https://openalex.org/W2804621595","https://openalex.org/W2889050557","https://openalex.org/W2902836694","https://openalex.org/W2917887692","https://openalex.org/W2924007842","https://openalex.org/W2953853258","https://openalex.org/W2962780596","https://openalex.org/W2963557052","https://openalex.org/W2963669509","https://openalex.org/W2963800363","https://openalex.org/W2963869461","https://openalex.org/W2964014798","https://openalex.org/W2964094607","https://openalex.org/W2990431681","https://openalex.org/W2995034616","https://openalex.org/W2999831383","https://openalex.org/W3136489197","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4244364093","https://openalex.org/W4225257263","https://openalex.org/W3091305751","https://openalex.org/W2892323418","https://openalex.org/W2539894906","https://openalex.org/W2110628090","https://openalex.org/W2073942616","https://openalex.org/W2052022131","https://openalex.org/W2047666046","https://openalex.org/W1988643100"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,14,28,74,95,108,126],"large-scale":[6,91],"detailed":[7,85,143],"3D":[8,24,37,50,67,75,121,137],"face":[9,25,122],"dataset,":[10,94],"FaceScape,":[11],"and":[12,43,81,92,151],"propose":[13],"novel":[15,96],"algorithm":[16,97],"that":[17,57],"is":[18,58,98],"able":[19],"to":[20,61,101,156],"predict":[21],"elaborate":[22],"riggable":[23,140],"models":[26,51,69,138],"from":[27,40,125],"single":[29,127],"image":[30,128],"input.":[31,129],"FaceScape":[32],"dataset":[33,150],"provides":[34],"18,760":[35],"textured":[36],"faces,":[38],"captured":[39],"938":[41],"subjects":[42],"each":[44],"with":[45,141],"20":[46],"specific":[47],"expressions.":[48,147],"The":[49,112,148],"contain":[52],"the":[53,90,103,117,132],"pore-level":[54],"facial":[55,68],"geometry":[56,144],"also":[59],"processed":[60],"be":[62,71,154],"topologically":[63],"uniformed.":[64],"These":[65],"fine":[66],"can":[70],"represented":[72],"as":[73,116],"morphable":[76],"model":[77],"for":[78,84,158],"rough":[79],"shapes":[80],"displacement":[82],"maps":[83],"geometry.":[86],"Taking":[87],"advantage":[88],"of":[89,119],"high-accuracy":[93],"further":[99],"proposed":[100],"learn":[102],"expression-specific":[104],"dynamic":[105],"details":[106],"using":[107],"deep":[109],"neural":[110],"network.":[111],"learned":[113],"relationship":[114],"serves":[115],"foundation":[118],"our":[120,135],"prediction":[123],"system":[124],"Different":[130],"than":[131],"previous":[133],"methods,":[134],"predicted":[136],"are":[139],"highly":[142],"under":[145],"different":[146],"unprecedented":[149],"code":[152],"will":[153],"released":[155],"public":[157],"research":[159],"purpose.":[160]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3034798648","counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":62},{"year":2023,"cited_by_count":75},{"year":2022,"cited_by_count":52},{"year":2021,"cited_by_count":39},{"year":2020,"cited_by_count":5}],"updated_date":"2025-04-20T11:04:32.354467","created_date":"2020-06-19"}