Neural Microfacet Fields for Inverse Rendering

Alexander Mai, Dor Verbin, Falko Kuester, Sara Fridovich-Keil; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 408-418

We present Neural Microfacet Fields, a method for recovering materials, geometry (volumetric density), and environmental illumination from a collection of images of a scene. Our method applies a microfacet reflectance model within a volumetric setting by treating each sample along the ray as a surface, rather than an emitter. Using surface-based Monte Carlo rendering in a volumetric setting enables our method to perform inverse rendering efficiently and enjoy recent advances in volume rendering. Our approach obtains similar performance as state-of-the-art methods for novel view synthesis and outperforms prior work in inverse rendering, capturing high fidelity geometry and high frequency illumination details.