Photometric Stereo using Gaussian Splatting and inverse rendering

Matéo Ducastel; David Tschumperlé; Yvain Quéau

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arXiv · 2507.06684

Photometric Stereo using Gaussian Splatting and inverse rendering

Matéo Ducastel·David Tschumperlé·Yvain Quéau

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Abstract

Recent state-of-the-art algorithms in photometric stereo rely on neural networks and operate either through prior learning or inverse rendering optimization. Here, we revisit the problem of calibrated photometric stereo by leveraging recent advances in 3D inverse rendering using the Gaussian Splatting formalism. This allows us to parameterize the 3D scene to be reconstructed and optimize it in a more interpretable manner. Our approach incorporates a simplified model for light representation and demonstrates the potential of the Gaussian Splatting rendering engine for the photometric stereo problem.

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Matéo Ducastel, David Tschumperlé, Yvain Quéau. 2025-07-09. Photometric Stereo using Gaussian Splatting and inverse rendering. https://arxiv.org/abs/2507.06684

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