Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

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 …

Decomposing a scene into its shape, reflectance and illumination is a fundamental problem
in computer vision and graphics. Neural approaches such as NeRF have achieved …

We present Neural Reflectance Fields, a novel deep scene representation that encodes
volume density, normal and reflectance properties at any 3D point in a scene using a fully …

Traditional multi-view photometric stereo (MVPS) methods are often composed of multiple
disjoint stages, resulting in noticeable accumulated errors. In this paper, we present a neural …

We present" The Relightables", a volumetric capture system for photorealistic and high
quality relightable full-body performance capture. While significant progress has been made …

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 …

We propose a deep inverse rendering framework for indoor scenes. From a single RGB
image of an arbitrary indoor scene, we obtain a complete scene reconstruction, estimating …

Over the last years, with the advent of Generative Adversarial Networks (GANs), many face
analysis tasks have accomplished astounding performance, with applications including, but …

Reconstructing shape and reflectance properties from images is a highly under-constrained
problem, and has previously been addressed by using specialized hardware to capture …