ReN Human: Learning Relightable Neural Implicit Surfaces for Animatable Human Rendering
DescriptionThis work proposes ReN Human, a framework that utilizes sparse or even monocular input videos to reconstruct a 3D human model represented as a deformable implicit neural surface. It decomposes geometry and material, resulting in a relightable, animatable human model that can be rendered with novel views, poses, and lighting.
Event Type
Technical Papers
TimeWednesday, 4 December 202411:43am - 11:54am JST
LocationHall B5 (2), B Block, Level 5
