{"id":"https://openalex.org/W7167226615","doi":"https://doi.org/10.1145/3811303","title":"Learning a Delighting Prior for Facial Appearance Capture in the Wild","display_name":"Learning a Delighting Prior for Facial Appearance Capture in the Wild","publication_year":2026,"publication_date":"2026-07-03","ids":{"openalex":"https://openalex.org/W7167226615","doi":"https://doi.org/10.1145/3811303"},"language":"en","primary_location":{"id":"doi:10.1145/3811303","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811303","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/10.1145/3811303","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101948400","display_name":"Yuxuan Han","orcid":"https://orcid.org/0000-0002-2844-5074"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Han","raw_affiliation_strings":["School of Software and BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2844-5074","affiliations":[{"raw_affiliation_string":"School of Software and BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129674653","display_name":"Xin Ming","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Ming","raw_affiliation_strings":["School of Software and BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-9602-6078","affiliations":[{"raw_affiliation_string":"School of Software and BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100689730","display_name":"Tianxiao Li","orcid":"https://orcid.org/0000-0002-9147-7511"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiao Li","raw_affiliation_strings":["School of Software and BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-5136-6005","affiliations":[{"raw_affiliation_string":"School of Software and BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139982929","display_name":"Zhuofan Shen","orcid":"https://orcid.org/0009-0000-5737-4917"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuofan Shen","raw_affiliation_strings":["School of Software and BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-5737-4917","affiliations":[{"raw_affiliation_string":"School of Software and BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038142929","display_name":"Qixuan Zhang","orcid":"https://orcid.org/0000-0002-4837-7152"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]},{"id":"https://openalex.org/I4210150405","display_name":"Hongzhiwei Technology (China)","ror":"https://ror.org/04bapa014","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210150405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qixuan Zhang","raw_affiliation_strings":["Deemos Technology Co., Ltd., Shanghai, China","ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4837-7152","affiliations":[{"raw_affiliation_string":"Deemos Technology Co., Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210150405"]},{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100777698","display_name":"Lan Xu","orcid":"https://orcid.org/0000-0002-8807-7787"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Xu","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8807-7787","affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035609529","display_name":"Feng Xu","orcid":"https://orcid.org/0000-0002-0953-1057"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xu","raw_affiliation_strings":["School of Software and BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0953-1057","affiliations":[{"raw_affiliation_string":"School of Software and BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.88795618,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"4","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.7996000051498413,"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":0.7996000051498413,"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":0.12800000607967377,"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":0.011099999770522118,"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/leverage","display_name":"Leverage (statistics)","score":0.6585000157356262},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6047999858856201},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4778999984264374},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.42989999055862427},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4124000072479248},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.38659998774528503},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.33640000224113464},{"id":"https://openalex.org/keywords/pencil","display_name":"Pencil (optics)","score":0.319599986076355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8059999942779541},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6585000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6172000169754028},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6047999858856201},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4778999984264374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44190001487731934},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.42989999055862427},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4124000072479248},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.38659998774528503},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C134949993","wikidata":"https://www.wikidata.org/wiki/Q2068617","display_name":"Pencil (optics)","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.30219998955726624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3003000020980835},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C90697248","wikidata":"https://www.wikidata.org/wiki/Q1062896","display_name":"Character animation","level":4,"score":0.28850001096725464},{"id":"https://openalex.org/C138591656","wikidata":"https://www.wikidata.org/wiki/Q5157538","display_name":"Computer facial animation","level":4,"score":0.2872999906539917},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C104582849","wikidata":"https://www.wikidata.org/wiki/Q787282","display_name":"Automatic identification and data capture","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.27619999647140503},{"id":"https://openalex.org/C55457006","wikidata":"https://www.wikidata.org/wiki/Q3647098","display_name":"Kinesthetic learning","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2637999951839447}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3811303","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811303","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:10.1145/3811303","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3811303","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":45,"referenced_works":["https://openalex.org/W1961571273","https://openalex.org/W1987875999","https://openalex.org/W2052248973","https://openalex.org/W2105649179","https://openalex.org/W2126733192","https://openalex.org/W2164389014","https://openalex.org/W2235136907","https://openalex.org/W2866634454","https://openalex.org/W2949662773","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W3000731301","https://openalex.org/W3015873132","https://openalex.org/W3034771054","https://openalex.org/W3035413889","https://openalex.org/W3048401767","https://openalex.org/W3106984321","https://openalex.org/W3110182603","https://openalex.org/W3164455552","https://openalex.org/W3168518331","https://openalex.org/W3213346804","https://openalex.org/W4309803402","https://openalex.org/W4312731964","https://openalex.org/W4313130906","https://openalex.org/W4372283500","https://openalex.org/W4386065574","https://openalex.org/W4386065822","https://openalex.org/W4386071504","https://openalex.org/W4386071752","https://openalex.org/W4386075618","https://openalex.org/W4386076478","https://openalex.org/W4387994527","https://openalex.org/W4388045447","https://openalex.org/W4390872725","https://openalex.org/W4390873689","https://openalex.org/W4393248012","https://openalex.org/W4400573496","https://openalex.org/W4402703056","https://openalex.org/W4402703063","https://openalex.org/W4402753643","https://openalex.org/W4403820694","https://openalex.org/W4404525944","https://openalex.org/W4409262871","https://openalex.org/W4415795929","https://openalex.org/W4417125073"],"related_works":[],"abstract_inverted_index":{"High-quality":[0],"facial":[1,173],"appearance":[2,121,144],"capture":[3,122,145,174],"has":[4],"traditionally":[5],"required":[6],"costly":[7],"studio":[8],"recording.":[9],"Recent":[10],"works":[11],"consider":[12],"an":[13],"in-the-wild":[14],"smartphone-based":[15],"setup;":[16],"however,":[17],"their":[18],"model-based":[19],"inverse":[20],"rendering":[21],"paradigm":[22,42],"struggles":[23],"with":[24],"the":[25,41,54,58,62,85,101,149,167,181],"complex":[26],"disentanglement":[27],"of":[28,103,158],"reflectance":[29,127],"from":[30,96,129],"unknown":[31],"illumination.":[32],"To":[33],"bridge":[34],"this":[35],"gap,":[36],"we":[37,92,141,170],"propose":[38,70],"to":[39,52,75,147,184],"shift":[40],"into":[43,153],"training":[44],"a":[45,50,104,117,137,155,177],"powerful":[46,113],"delighting":[47,98,105,114],"network":[48,87],"as":[49],"prior":[51,106,115,134],"constrain":[53],"optimization.":[55],"We":[56],"leverage":[57,142],"OLAT":[59],"dataset":[60,152],"and":[61,69,119,166,175],"rendered":[63],"Light":[64],"Stage":[65],"scans":[66],"for":[67,180],"training,":[68],"Dataset":[71],"Latent":[72],"Modulation":[73],"(DLM)":[74],"seamlessly":[76],"integrate":[77],"these":[78],"heterogeneous":[79],"data":[80],"sources.":[81],"Specifically,":[82],"by":[83,136],"conditioning":[84],"core":[86],"on":[88],"learnable":[89],"source-aware":[90],"tokens,":[91],"decouple":[93],"dataset-specific":[94],"styles":[95],"physical":[97],"principles,":[99],"enabling":[100],"emergence":[102],"that":[107,124],"outperforms":[108],"existing":[109],"proprietary":[110],"models.":[111],"This":[112],"enables":[116],"simple":[118],"automatic":[120],"pipeline":[123],"achieves":[125],"high-quality":[126],"estimation":[128],"casual":[130],"video":[131],"inputs,":[132],"outperforming":[133],"arts":[135],"large":[138],"margin.":[139],"Furthermore,":[140],"our":[143,164],"method":[146],"transform":[148],"multi-view":[150],"NeRSemble":[151],"NeRSemble-Scan,":[154],"large-scale":[156],"collection":[157],"4K-resolution":[159],"relightable":[160],"scans.":[161],"By":[162],"open-sourcing":[163],"model":[165],"NeRSemble-Scan":[168],"dataset,":[169],"democratize":[171],"high-end":[172],"provide":[176],"new":[178],"foundation":[179],"research":[182],"community":[183],"build":[185],"photorealistic":[186],"digital":[187],"humans.":[188]},"counts_by_year":[],"updated_date":"2026-07-04T06:14:54.683239","created_date":"2026-07-04T00:00:00"}
