We present GaussianAvatar an efficient approach to creating realistic human avatars with
dynamic 3D appearances from a single video. We start by introducing animatable 3D …

Modeling animatable human avatars from RGB videos is a long-standing and challenging
problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent …

Abstract We present\emph {DreamHuman}, a method to generate realistic animatable 3D
human avatar models entirely from textual descriptions. Recent text-to-3D methods have …

We present AvatarReX, a new method for learning NeRF-based full-body avatars from video
data. The learnt avatar not only provides expressive control of the body, hands and the face …

This work addresses the problem of real-time rendering of photorealistic human body
avatars learned from multi-view videos. While the classical approaches to model and render …

Creating expressive, diverse and high-quality 3D avatars from highly customized text
descriptions and pose guidance is a challenging task, due to the intricacy of modeling and …

Modeling and rendering photorealistic avatars is of crucial importance in many applications.
Existing methods that build a 3D avatar from visual observations, however, struggle to …

We present CaPhy, a novel method for reconstructing animatable human avatars with
realistic dynamic properties for clothing. Specifically, we aim for capturing the geometric and …

This paper tackles the problem of creating relightable and animatable neural avatars from
sparse-view (or monocular) videos of dynamic humans under unknown illumination …

In this work, we propose a novel clothed human reconstruction method called
GaussianBody, based on 3D Gaussian Splatting. Compared with the costly neural radiance …