We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike
NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which …

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 …

Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …

We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct
neural radiance fields for view synthesis. Unlike prior works on neural radiance fields that …

We propose TensoIR, a novel inverse rendering approach based on tensor factorization and
neural fields. Unlike previous works that use purely MLP-based neural fields, thus suffering …

We present a method to perform novel view and time synthesis of dynamic scenes, requiring
only a monocular video with known camera poses as input. To do this, we introduce Neural …

We present a method that takes as input a set of images of a scene illuminated by
unconstrained known lighting, and produces as output a 3D representation that can be …

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

Decomposing a scene into its shape, reflectance, and illumination is a challenging but
important problem in computer vision and graphics. This problem is inherently more …

We propose a novel approach for 3D video synthesis that is able to represent multi-view
video recordings of a dynamic real-world scene in a compact, yet expressive representation …