Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation

Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, H. Cai +5 more
2/14/2026

No official code found. Best implementation: lwwu2/fipt (62 stars, MIT, last commit 2025-01-11).

Abstract

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

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Code Implementations(1)

lwwu2/fiptCommunity100%
MIT

FIPT: Factorized Inverse Path Tracing

626Shell, PythonMar 9, 20231 years agoMIT

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Cite this paper

@article{wu2026factorized,
  title  = {Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation},
  author = {Liwen Wu and Rui Zhu and Mustafa B. Yaldiz and Yinhao Zhu and H. Cai and J. Matai and F. Porikli and Tzu-Mao Li and Manmohan Chandraker and R. Ramamoorthi},
  year   = {2026},
  eprint = {2304.05669},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2304.05669},
  journal = {ICCV 2023 2023}
}

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