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 …

Reconstructing an object's geometry and appearance from multiple images, also known as
inverse rendering, is a fundamental problem in computer graphics and vision. Inverse …

Controlled capture of real‐world material appearance yields tabulated sets of highly realistic
reflectance data. In practice, however, its high memory footprint requires compressing into a …

Neural fields have gained significant attention in the computer vision community due to their
excellent performance in novel view synthesis, geometry reconstruction, and generative …

We introduce a novel multi-view stereo (MVS) method that can simultaneously recover not
just per-pixel depth but also surface normals, together with the reflectance of textureless …

We propose a differentiable rendering algorithm for efficient novel view synthesis. By
departing from volume-based representations in favor of a learned point representation, we …

Reflectance bounds the frequency spectrum of illumination in the object appearance. In this
paper we introduce the first stochastic inverse rendering method which recovers the …

We describe a novel approach to decompose a single panorama of an empty indoor
environment into four appearance components: specular, direct sunlight, diffuse and diffuse …

Environment maps are commonly used to represent and compute far‐field illumination in
virtual scenes. However, they are expensive to evaluate and sample from, limiting their …

Recent neural rendering methods have demonstrated accurate view interpolation by
predicting volumetric density and color with a neural network. Although such volumetric …