Abstract
Modern computer vision algorithms have brought significant advancement to 3D geometry reconstruction. However, illumination and material reconstruction remain less
studied, with current approaches assuming very simplified
models for materials and illumination. We introduce Inverse Path Tracing, a novel approach to jointly estimate the
material properties of objects and light sources in indoor
scenes by using an invertible light transport simulation. We
assume a coarse geometry scan, along with corresponding
images and camera poses. The key contribution of this work
is an accurate and simultaneous retrieval of light sources
and physically based material properties (e.g., diffuse re-
flectance, specular reflectance, roughness, etc.) for the purpose of editing and re-rendering the scene under new conditions. To this end, we introduce a novel optimization method
using a differentiable Monte Carlo renderer that computes
derivatives with respect to the estimated unknown illumination and material properties. This enables joint optimization for physically correct light transport and material models using a tailored stochastic gradient descent.