{"id":"https://openalex.org/W4417000808","doi":"https://doi.org/10.1145/3763300","title":"Generative Head-Mounted Camera Captures for Photorealistic Avatars","display_name":"Generative Head-Mounted Camera Captures for Photorealistic Avatars","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4417000808","doi":"https://doi.org/10.1145/3763300"},"language":"en","primary_location":{"id":"doi:10.1145/3763300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3763300","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3763300","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029659931","display_name":"Shaojie Bai","orcid":"https://orcid.org/0009-0001-7969-9429"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaojie Bai","raw_affiliation_strings":["Meta Reality Labs, San Francisco, USA"],"raw_orcid":"https://orcid.org/0009-0001-7969-9429","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, San Francisco, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053512282","display_name":"Seunghyeon Seo","orcid":"https://orcid.org/0009-0007-8527-1561"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghyeon Seo","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0007-8527-1561","affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064176415","display_name":"Youde WANG","orcid":"https://orcid.org/0009-0002-1723-0729"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yida Wang","raw_affiliation_strings":["Meta Reality Labs, Vancouver, Canada"],"raw_orcid":"https://orcid.org/0009-0002-1723-0729","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Vancouver, Canada","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chenghui Li","orcid":"https://orcid.org/0009-0003-7055-5757"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenghui Li","raw_affiliation_strings":["Meta Reality Labs, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0009-0003-7055-5757","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Pittsburgh, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014795461","display_name":"Owen Wang","orcid":"https://orcid.org/0009-0006-3552-1625"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Owen Wang","raw_affiliation_strings":["Meta Reality Labs, Burlingame, USA"],"raw_orcid":"https://orcid.org/0009-0006-3552-1625","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Burlingame, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043944858","display_name":"Te-Li Wang","orcid":"https://orcid.org/0009-0005-1690-6928"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Te-Li Wang","raw_affiliation_strings":["Meta Reality Labs, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0009-0005-1690-6928","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Pittsburgh, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082152626","display_name":"Tianyang Ma","orcid":"https://orcid.org/0009-0000-2400-2682"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyang Ma","raw_affiliation_strings":["Meta Reality Labs, Burlingame, USA"],"raw_orcid":"https://orcid.org/0009-0000-2400-2682","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Burlingame, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082178717","display_name":"Jason Saragih","orcid":"https://orcid.org/0000-0001-6218-5029"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Saragih","raw_affiliation_strings":["Meta Reality Labs, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0000-0001-6218-5029","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Pittsburgh, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shih-En Wei","orcid":"https://orcid.org/0000-0002-0092-3441"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shih-En Wei","raw_affiliation_strings":["Meta Reality Labs, Pittsburgh, USA"],"raw_orcid":"https://orcid.org/0000-0002-0092-3441","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Pittsburgh, USA","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084897975","display_name":"Nojun Kwak","orcid":"https://orcid.org/0000-0002-1792-0327"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Nojun Kwak","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-1792-0327","affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100302603","display_name":"Hyung Jun Kim","orcid":"https://orcid.org/0009-0009-2973-0676"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyung Jun(John) Kim","raw_affiliation_strings":["Meta Reality Labs, Burlingame, USA"],"raw_orcid":"https://orcid.org/0009-0009-2973-0676","affiliations":[{"raw_affiliation_string":"Meta Reality Labs, Burlingame, USA","institution_ids":["https://openalex.org/I4210128585"]}]}],"institutions":[],"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":0.35234249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"44","issue":"6","first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.8156999945640564,"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":0.8156999945640564,"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":0.13009999692440033,"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/T11094","display_name":"Face Recognition and Perception","score":0.02019999921321869,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/avatar","display_name":"Avatar","score":0.6392999887466431},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6065999865531921},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5569000244140625},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5273000001907349},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5049999952316284},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.46970000863075256},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42410001158714294},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4221999943256378}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8346999883651733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.675599992275238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6435999870300293},{"id":"https://openalex.org/C2777365542","wikidata":"https://www.wikidata.org/wiki/Q83090","display_name":"Avatar","level":2,"score":0.6392999887466431},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6065999865531921},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5569000244140625},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5273000001907349},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5049999952316284},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.46970000863075256},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4221999943256378},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C502989409","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Animation","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C138591656","wikidata":"https://www.wikidata.org/wiki/Q5157538","display_name":"Computer facial animation","level":4,"score":0.31060001254081726},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C2776684213","wikidata":"https://www.wikidata.org/wiki/Q6007582","display_name":"Impression","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3763300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3763300","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3763300","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3763300","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1975848997","https://openalex.org/W2013871799","https://openalex.org/W2016462422","https://openalex.org/W2039239232","https://openalex.org/W2126733192","https://openalex.org/W2152826865","https://openalex.org/W2235136907","https://openalex.org/W2237250383","https://openalex.org/W2259424905","https://openalex.org/W2431874326","https://openalex.org/W2471370490","https://openalex.org/W2556634673","https://openalex.org/W2739385919","https://openalex.org/W2743627947","https://openalex.org/W2810084975","https://openalex.org/W2811426698","https://openalex.org/W2912459656","https://openalex.org/W2946584893","https://openalex.org/W2982083293","https://openalex.org/W3048381483","https://openalex.org/W3172500391","https://openalex.org/W3184291866","https://openalex.org/W4210279013","https://openalex.org/W4231633165","https://openalex.org/W4286611181","https://openalex.org/W4312578889","https://openalex.org/W4312933868","https://openalex.org/W4362641980","https://openalex.org/W4386057725","https://openalex.org/W4389539479","https://openalex.org/W4390873054"],"related_works":[],"abstract_inverted_index":{"Enabling":[0],"photorealistic":[1],"avatar":[2,150],"animations":[3],"in":[4,42,80],"virtual":[5],"and":[6,45,78,91,113,173,209,224],"augmented":[7],"reality":[8],"(VR/AR)":[9],"has":[10,39],"been":[11],"challenging":[12],"because":[13],"of":[14,17,22,48,86],"the":[15,94,165,193,196],"difficulty":[16],"obtaining":[18],"ground":[19,69,182],"truth":[20],"state":[21,151],"faces.":[23],"It":[24],"is":[25,160],"physically":[26],"impossible":[27],"to":[28,101,138,140,162,179,189],"obtain":[29],"synchronized":[30],"images":[31,146,208],"from":[32,73,152,175,214],"head-mounted":[33],"cameras":[34],"(HMC)":[35],"sensing":[36],"input,":[37],"which":[38,52,105,134,219],"partial":[40],"observations":[41,55],"infrared":[43],"(IR),":[44],"an":[46],"array":[47],"outside-in":[49],"dome":[50,153],"cameras,":[51],"have":[53],"full":[54],"that":[56,127,157,169],"match":[57],"avatars'":[58],"appearance.":[59],"Prior":[60],"works":[61],"relying":[62],"on":[63,195],"analysis-by-synthesis":[64],"methods":[65],"could":[66],"generate":[67,142],"accurate":[68,181],"truth,":[70],"but":[71],"suffer":[72],"imperfect":[74],"disentanglement":[75],"between":[76],"expression":[77,172],"style":[79],"their":[81],"personalized":[82],"training.":[83],"The":[84],"reliance":[85,194],"extensive":[87],"paired":[88,197],"captures":[89,132],"(HMC":[90],"dome)":[92],"for":[93,109],"same":[95],"subject":[96],"makes":[97],"it":[98],"operationally":[99],"expensive":[100],"collect":[102],"large-scale":[103],"datasets,":[104],"cannot":[106],"be":[107],"reused":[108],"different":[110],"HMC":[111,125,131,145,207],"viewpoints":[112],"lighting.":[114],"In":[115],"this":[116],"work,":[117],"we":[118],"propose":[119],"a":[120],"novel":[121],"generative":[122],"approach,":[123],"Generative":[124],"(GenHMC),":[126],"leverages":[128],"large":[129],"unpaired":[130],",":[133],"are":[135],"much":[136],"easier":[137],"collect,":[139],"directly":[141],"high-quality":[143],"synthetic":[144,206],"given":[147],"any":[148],"conditioning":[149,167],"captures.":[154,198],"We":[155,199],"show":[156],"our":[158,185],"method":[159,186],"able":[161],"properly":[163],"disentangle":[164],"input":[166],"signal":[168],"specifies":[170],"facial":[171,176],"viewpoint,":[174],"appearance,":[177],"leading":[178],"more":[180],"truth.":[183],"Furthermore,":[184],"can":[187],"generalize":[188],"unseen":[190],"identities,":[191],"removing":[192],"demonstrate":[200],"these":[201,215],"breakthroughs":[202],"by":[203],"both":[204],"evaluating":[205],"universal":[210],"face":[211],"encoders":[212],"trained":[213],"new":[216],"HMC-avatar":[217],"correspondences,":[218],"achieve":[220],"better":[221],"data":[222],"efficiency":[223],"state-of-the-art":[225],"accuracy.":[226]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-04T00:00:00"}