4 citations · 6 across the 7 of their papers we have counts for
7 papers
Gaussian Pixel Codec Avatars: A Hybrid Representation for Efficient Rendering
Divam Gupta, Anuj Pahuja, Nemanja Bartolovic +3
We present Gaussian Pixel Codec Avatars (GPiCA), photorealistic head avatars that can be generated from multi-view images and efficiently rendered on mobile devices. GPiCA utilizes…
HairCUP: Hair Compositional Universal Prior for 3D Gaussian Avatars
Byungjun Kim, Shunsuke Saito, Giljoo Nam +4
We present a universal prior model for 3D head avatars with explicit hair compositionality. Existing approaches to build generalizable priors for 3D head avatars often adopt a holi…
Relightable Full-Body Gaussian Codec Avatars
Shaofei Wang, Tomas Simon, Igor Santesteban +15
We propose Relightable Full-Body Gaussian Codec Avatars, a new approach for modeling relightable full-body avatars with fine-grained details including face and hands. The unique ch…
SqueezeMe: Mobile-Ready Distillation of Gaussian Full-Body Avatars
Forrest Iandola, Stanislav Pidhorskyi, Igor Santesteban +7
Gaussian-based human avatars have achieved an unprecedented level of visual fidelity. However, existing approaches based on high-capacity neural networks typically require a deskto…
URHand: Universal Relightable Hands
Zhaoxi Chen, Gyeongsik Moon, Kaiwen Guo +20
Existing photorealistic relightable hand models require extensive identity-specific observations in different views, poses, and illuminations, and face challenges in generalizing t…
Relightable Gaussian Codec Avatars
Shunsuke Saito, Gabriel Schwartz, Tomas Simon +2
The fidelity of relighting is bounded by both geometry and appearance representations. For geometry, both mesh and volumetric approaches have difficulty modeling intricate structur…
A Dataset of Relighted 3D Interacting Hands
Gyeongsik Moon, Shunsuke Saito, Weipeng Xu +12
The two-hand interaction is one of the most challenging signals to analyze due to the self-similarity, complicated articulations, and occlusions of hands. Although several datasets…