Novel view synthesis for dynamic scenes is still a challenging problem in computer vision
and graphics. Recently Gaussian splatting has emerged as a robust technique to represent …

Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great
potential in novel view synthesis of a scene. However, current NeRF-based methods cannot …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

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 …

Unsupervised learning of 3D-aware generative adversarial networks (GANs) using only
collections of single-view 2D photographs has very recently made much progress. These 3D …

Creation of 3D content by stylization is a promising yet challenging problem in computer
vision and graphics research. In this work, we focus on stylizing photorealistic appearance …

We present a technique for automatically producing a deformation of an input triangle mesh,
guided solely by a text prompt. Our framework is capable of deformations that produce both …

In this paper, we focus on category-level 6D pose and size estimation from a monocular
RGB-D image. Previous methods suffer from inefficient category-level pose feature …

Recent advances in radiance fields enable photorealistic rendering of static or dynamic 3D
scenes, but still do not support explicit deformation that is used for scene manipulation or …

Mesh generation is of great value in various applications involving computer graphics and
virtual content, yet designing generative models for meshes is challenging due to their …