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 …

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 …

Abstract Neural Radiance Field (NeRF) has recently emerged as a powerful representation
to synthesize photorealistic novel views. While showing impressive performance, it relies on …

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 …

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable
many applications such as relighting and virtual object insertion. Recent NeRF based …

Novel view synthesis from unconstrained in-the-wild images remains a meaningful but
challenging task. The photometric variation and transient occluders in those unconstrained …

Recent advances in neural radiance fields have enabled the high-fidelity 3D reconstruction
of complex scenes for novel view synthesis. However, it remains underexplored how the …

Inverse rendering of an object under entirely unknown capture conditions is a fundamental
challenge in computer vision and graphics. Neural approaches such as NeRF have …

Abstract Neural Radiance Fields (NeRFs) are a powerful representation for modeling a 3D
scene as a continuous function. Though NeRF is able to render complex 3D scenes with …