Abstract Recently 3D Gaussian Splatting has demonstrated impressive novel view synthesis
results reaching high fidelity and efficiency. However strong artifacts can be observed when …

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 …

We present a method that simultaneously addresses the tasks of dynamic scene novel-view
synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We …

We introduce an approach that creates animatable human avatars from monocular videos
using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields …

Reconstructing dynamic objects from monocular videos is a severely underconstrained and
challenging problem and recent work has approached it in various directions. However …

We present a method that simultaneously addresses the tasks of dynamic scene novel-view
synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We …

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 …

We present Drivable 3D Gaussian Avatars (D3GA), the first 3D controllable model for human
bodies rendered with Gaussian splats. Current photorealistic drivable avatars require either …

We have recently seen tremendous progress in photo-real human modeling and rendering.
Yet efficiently rendering realistic human performance and integrating it into the rasterization …