{"id":"https://openalex.org/W4416060667","doi":"https://doi.org/10.48550/arxiv.2507.05620","title":"Generative Head-Mounted Camera Captures for Photorealistic Avatars","display_name":"Generative Head-Mounted Camera Captures for Photorealistic Avatars","publication_year":2025,"publication_date":"2025-07-08","ids":{"openalex":"https://openalex.org/W4416060667","doi":"https://doi.org/10.48550/arxiv.2507.05620"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2507.05620","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05620","pdf_url":"https://arxiv.org/pdf/2507.05620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.05620","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037832036","display_name":"Shaojie Bai","orcid":"https://orcid.org/0009-0006-7526-5216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Shaojie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053512282","display_name":"Seunghyeon Seo","orcid":"https://orcid.org/0009-0007-8527-1561"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seo, Seunghyeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079490872","display_name":"Yida Wang","orcid":"https://orcid.org/0000-0003-4519-9108"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yida","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120746598","display_name":"Chenghui Li","orcid":"https://orcid.org/0009-0002-5899-3511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chenghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014795461","display_name":"Owen Wang","orcid":"https://orcid.org/0009-0006-3552-1625"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Owen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043944858","display_name":"Te-Li Wang","orcid":"https://orcid.org/0009-0005-1690-6928"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Te-Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082152626","display_name":"Tianyang Ma","orcid":"https://orcid.org/0009-0000-2400-2682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Tianyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082178717","display_name":"Jason Saragih","orcid":"https://orcid.org/0000-0001-6218-5029"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saragih, Jason","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071340306","display_name":"Shih-En Wei","orcid":"https://orcid.org/0000-0002-3214-125X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Shih-En","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084897975","display_name":"Nojun Kwak","orcid":"https://orcid.org/0000-0002-1792-0327"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwak, Nojun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100302603","display_name":"Hyung Jun Kim","orcid":"https://orcid.org/0009-0009-2973-0676"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Hyung Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.8346999883651733,"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":0.8346999883651733,"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":0.09989999979734421,"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":0.025499999523162842,"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":0.6349999904632568},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5931000113487244},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.544700026512146},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5199999809265137},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5016000270843506},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.4896000027656555},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4812000095844269},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4156999886035919},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.40639999508857727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8072999715805054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6951000094413757},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6621999740600586},{"id":"https://openalex.org/C2777365542","wikidata":"https://www.wikidata.org/wiki/Q83090","display_name":"Avatar","level":2,"score":0.6349999904632568},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.544700026512146},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5199999809265137},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5016000270843506},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4812000095844269},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.40639999508857727},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C502989409","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Animation","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.29330000281333923},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C2776684213","wikidata":"https://www.wikidata.org/wiki/Q6007582","display_name":"Impression","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C138591656","wikidata":"https://www.wikidata.org/wiki/Q5157538","display_name":"Computer facial animation","level":4,"score":0.2612000107765198}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2507.05620","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05620","pdf_url":"https://arxiv.org/pdf/2507.05620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.05620","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.05620","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.05620","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.05620","pdf_url":"https://arxiv.org/pdf/2507.05620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Enabling":[0],"photorealistic":[1],"avatar":[2,149],"animations":[3],"in":[4,42,80],"virtual":[5],"and":[6,45,78,91,113,172,208,223],"augmented":[7],"reality":[8],"(VR/AR)":[9],"has":[10,39],"been":[11],"challenging":[12],"because":[13],"of":[14,17,22,48,86],"the":[15,94,164,192,195],"difficulty":[16],"obtaining":[18],"ground":[19,69,181],"truth":[20],"state":[21,150],"faces.":[23],"It":[24],"is":[25,159],"physically":[26],"impossible":[27],"to":[28,101,137,139,161,178,188],"obtain":[29],"synchronized":[30],"images":[31,145,207],"from":[32,73,151,174,213],"head-mounted":[33],"cameras":[34],"(HMC)":[35],"sensing":[36],"input,":[37],"which":[38,52,105,133,218],"partial":[40],"observations":[41,55],"infrared":[43],"(IR),":[44],"an":[46],"array":[47],"outside-in":[49],"dome":[50,152],"cameras,":[51],"have":[53],"full":[54],"that":[56,127,156,168],"match":[57],"avatars'":[58],"appearance.":[59],"Prior":[60],"works":[61],"relying":[62],"on":[63,194],"analysis-by-synthesis":[64],"methods":[65],"could":[66],"generate":[67,141],"accurate":[68,180],"truth,":[70],"but":[71],"suffer":[72],"imperfect":[74],"disentanglement":[75],"between":[76],"expression":[77,171],"style":[79],"their":[81],"personalized":[82],"training.":[83],"The":[84],"reliance":[85,193],"extensive":[87],"paired":[88,196],"captures":[89],"(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":[111,125,131,144,206],"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],"captures,":[132],"are":[134],"much":[135],"easier":[136],"collect,":[138],"directly":[140],"high-quality":[142],"synthetic":[143,205],"given":[146],"any":[147],"conditioning":[148,166],"captures.":[153,197],"We":[154,198],"show":[155],"our":[157,184],"method":[158,185],"able":[160],"properly":[162],"disentangle":[163],"input":[165],"signal":[167],"specifies":[169],"facial":[170,175],"viewpoint,":[173],"appearance,":[176],"leading":[177],"more":[179],"truth.":[182],"Furthermore,":[183],"can":[186],"generalize":[187],"unseen":[189],"identities,":[190],"removing":[191],"demonstrate":[199],"these":[200,214],"breakthroughs":[201],"by":[202],"both":[203],"evaluating":[204],"universal":[209],"face":[210],"encoders":[211],"trained":[212],"new":[215],"HMC-avatar":[216],"correspondences,":[217],"achieve":[219],"better":[220],"data":[221],"efficiency":[222],"state-of-the-art":[224],"accuracy.":[225]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
