Photometric Stereo Using Gaussian Splatting and Inverse Rendering
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. Through a proof-of-concept on the Lambertian reflectance case, our approach demonstrates the potential of the Gaussian Splatting rendering engine for the single view photometric stereo problem by accurately estimating the shape of the object.
Fields of Study & Subjects
Computer Graphics and Visualization Techniques
Advanced Vision and Imaging
3D Shape Modeling and Analysis
Publication details
- Journal / source
- ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Publisher
- IEEE
- Pages
- 9867–9871
- Publication date
- 21 April 2026
- Language
- EN