BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Asia/Seoul X-LIC-LOCATION:Asia/Seoul BEGIN:STANDARD TZOFFSETFROM:+0900 TZOFFSETTO:+0900 TZNAME:KST DTSTART:18871231T000000 DTSTART:19881009T020000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20230103T035308Z LOCATION:Room 324\, Level 3\, West Wing DTSTART;TZID=Asia/Seoul:20221207T110000 DTEND;TZID=Asia/Seoul:20221207T123000 UID:siggraphasia_SIGGRAPH Asia 2022_sess158_papers_421@linklings.com SUMMARY:Reconstructing Personalized Semantic Facial NeRF Models From Monoc ular Video DESCRIPTION:Technical Papers\n\nReconstructing Personalized Semantic Facia l NeRF Models From Monocular Video\n\nGao, Zhong, Xiang, Hong, Guo...\n\nW e present a novel semantic model for human head defined with neural radian ce field. The 3D-consistent head model consist of a set of disentangled an d interpretable bases, and can be driven by low-dimensional expression coe fficients. Thanks to the powerful representation ability of neural radianc e field, the constructed model can represent complex facial attributes inc luding hair, wearings, which can not be represented by traditional mesh bl endshape. To construct the personalized semantic facial model, we propose to define the bases as several multi-level voxel fields. With a short mono cular RGB video as input, our method can construct the subject's semantic facial NeRF model with only ten to twenty minutes, and can render a photo- realistic human head image in tens of miliseconds with a given expression coefficient and view direction. With this novel representation, we apply i t to many tasks like facial retargeting and expression editing. Experiment al results demonstrate its strong representation ability and training/infe rence speed.\n\nRegistration Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLa nguage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAND URL:https://sa2022.siggraph.org/en/full-program/?id=papers_421&sess=sess15 8 END:VEVENT END:VCALENDAR