Photometric Stereo using Gaussian Splatting and inverse rendering
Journal:
arXiv
Published Date:
Jul 9, 2025
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.
