Scientific discovery and engineering design are currently limited by the time and cost of
physical experiments. Numerical simulations are an alternative approach but are usually …

We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian
Splatting. Gaussian Splatting has recently become very popular as it yields realistic …

We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a
scene and the collection of images used to reconstruct it, our method uses an image …

Rigorously testing autonomy systems is essential for making safe self-driving vehicles (SDV)
a reality. It requires one to generate safety critical scenarios beyond what can be collected …

The advent of neural 3D Gaussians has recently brought about a revolution in the field of
neural rendering facilitating the generation of high-quality renderings at real-time speeds …

Diffusion models have emerged as the state-of-the-art for image generation, among other
tasks. Here, we present an efficient diffusion-based model for 3D-aware generation of neural …

We present Tensor4D, an efficient yet effective approach to dynamic scene modeling. The
key of our solution is an efficient 4D tensor decomposition method so that the dynamic scene …

In this paper, we present a novel differentiable point-based rendering framework to achieve
photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla …

We present a method for reconstructing high-quality meshes of large unbounded real-world
scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural …

Neural radiance fields (NeRFs) refer to a suit of deep neural networks that are used to learn
and represent objects or scenes. Generally speaking, NeRFs have five main characters …