Differentiable Point-based Inverse Rendering
Authors: Hoon-Gyu Chung, Seokjun Choi, Seung-Hwan Baek

We present differentiable point-based inverse rendering DPIR an analysis-by-synthesis method that processes images captured under diverse illuminations to estimate shape and spatially-varying BRDF. To this end we adopt point-based rendering eliminating the need for multiple samplings per ray typical of volumetric rendering thus significantly enhancing the speed of inverse rendering. To realize this idea we devise a hybrid point-volumetric representation for geometry and a regularized basis-BRDF representation for reflectance. The hybrid geometric representation enables fast rendering through point-based splatting while retaining the geometric details and stability inherent to SDF-based representations. The regularized basis-BRDF mitigates the ill-posedness of inverse rendering stemming from limited light-view angular samples. We also propose an efficient shadow detection method using point-based shadow map rendering. Our extensive evaluations demonstrate that DPIR outperforms prior works in terms of reconstruction accuracy computational efficiency and memory footprint. Furthermore our explicit point-based representation and rendering enables intuitive geometry and reflectance editing.