Differentiable Polarized Path Tracing

Researchers at MPI Informatics introduced Differentiable Polarized Path Tracing (DPPT), a method that extends physically based differentiable rendering to polarized light, enabling stable gradient estimation for inverse rendering tasks such as 3D reconstruction and material estimation. By combining path replay with local caching, DPPT overcomes numerical instability caused by rank-deficient polarimetric operators, broadening the applicability of inverse rendering in complex scenes.

arXiv:2607.13265v1 Announce Type: new Abstract: Physically based differentiable rendering has proven to be a powerful tool for inverse rendering problems e.g., 3D reconstruction, reflectance estimation, lighting estimation . However, most existing methods operate solely on radiometric intensity, discarding valuable polarization cues that constrain scene geometry and material properties. While forward simulation of polarized light is well-defined via Mueller-Stokes calculus, extending reverse-mode differentiation to this domain presents significant challenges. The rank-deficient nature of common polarimetric operators, such as linear polarizers and diffuse reflections, violates the invertibility assumptions of standard gradient estimators like path replay backpropagation and results in numerical instability. We address this by proposing a robust, polarization-aware differentiable path tracing method. Our approach estimates unbiased gradients through a combination of path replay and local caching. This formulation enables efficient and stable optimization of material and lighting parameters in complex scenes, broadening the applicability of physically based inverse rendering. Project page: https://vcai.mpi-inf.mpg.de/projects/DPPT/