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VERSION:2.0
PRODID:Linklings LLC
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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:JST
DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20260817T171532Z
LOCATION:Hall B5 (2)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241204T114300
DTEND;TZID=Asia/Tokyo:20241204T115400
UID:siggraphasia_SIGGRAPH Asia 2024_sess113_tog_111@linklings.com
SUMMARY:ReN Human: Learning Relightable Neural Implicit Surfaces for Anima
 table Human Rendering
DESCRIPTION:Rengan Xie (State Key Laboratory of CAD&CG, Zhejiang Universit
 y); Kai Huang (Institute of Computing Technology, Chinese Academy of Scien
 ces; Zhejiang Lab); In-Young Cho (KRAFTON); Sen Yang (Zhejiang Lab); Wei C
 hen, Hujun Bao, and Wenting Zheng (State Key Laboratory of CAD&CG, Zhejian
 g University); Rong Li (Zhejiang University); and Yuchi Huo (State Key Lab
 oratory of CAD&CG, Zhejiang University; Zhejiang Lab)\n\nThis work propose
 s ReN Human, a framework that utilizes sparse or even monocular input vide
 os to reconstruct a 3D human model represented as a deformable implicit ne
 ural surface. It decomposes geometry and material, resulting in a relighta
 ble, animatable human model that can be rendered with novel views, poses, 
 and lighting.\n\nRegistration Category: Full Access, Full Access Supporter
 \n\nLanguage Format: English Language\n\nSession Chair: Forrester Cole (Go
 ogle)\n\n
URL:https://asia.siggraph.org/2024/program/?id=tog_111&sess=sess113
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