  We present Neural Microfacet Fields, a method for recovering materials,
geometry, and environment illumination from images of a scene. Our method uses
a microfacet reflectance model within a volumetric setting by treating each
sample along the ray as a (potentially non-opaque) surface. Using surface-based
Monte Carlo rendering in a volumetric setting enables our method to perform
inverse rendering efficiently by combining decades of research in surface-based
light transport with recent advances in volume rendering for view synthesis.
Our approach outperforms prior work in inverse rendering, capturing high
fidelity geometry and high frequency illumination details; its novel view
synthesis results are on par with state-of-the-art methods that do not recover
illumination or materials.
