Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation
This work improves indoor inverse rendering and relighting for applications like computer graphics and vision, though it is incremental as it builds on existing inverse path tracing methods.
The paper tackles the problem of joint material and lighting estimation in indoor scenes by addressing the computational expense and ambiguities in inverse path tracing, resulting in a method that outperforms state-of-the-art techniques in accuracy and reduces optimization time to less than an hour.
Inverse path tracing has recently been applied to joint material and lighting estimation, given geometry and multi-view HDR observations of an indoor scene. However, it has two major limitations: path tracing is expensive to compute, and ambiguities exist between reflection and emission. Our Factorized Inverse Path Tracing (FIPT) addresses these challenges by using a factored light transport formulation and finds emitters driven by rendering errors. Our algorithm enables accurate material and lighting optimization faster than previous work, and is more effective at resolving ambiguities. The exhaustive experiments on synthetic scenes show that our method (1) outperforms state-of-the-art indoor inverse rendering and relighting methods particularly in the presence of complex illumination effects; (2) speeds up inverse path tracing optimization to less than an hour. We further demonstrate robustness to noisy inputs through material and lighting estimates that allow plausible relighting in a real scene. The source code is available at: https://github.com/lwwu2/fipt