PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting
About
We present PhySG, an end-to-end inverse rendering pipeline that includes a fully differentiable renderer and can reconstruct geometry, materials, and illumination from scratch from a set of RGB input images. Our framework represents specular BRDFs and environmental illumination using mixtures of spherical Gaussians, and represents geometry as a signed distance function parameterized as a Multi-Layer Perceptron. The use of spherical Gaussians allows us to efficiently solve for approximate light transport, and our method works on scenes with challenging non-Lambertian reflectance captured under natural, static illumination. We demonstrate, with both synthetic and real data, that our reconstructions not only enable rendering of novel viewpoints, but also physics-based appearance editing of materials and illumination.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Novel View Synthesis | Blender (test) | PSNR20.6 | 37 | |
| Novel Scene Relighting | Stanford-ORB 1.0 (test) | PSNR-H21.81 | 26 | |
| Novel View Synthesis | NeRF Synthetic Blender (test) | Avg PSNR18.91 | 24 | |
| Novel View Synthesis | Stanford-ORB 1.0 (test) | PSNR-H24.24 | 18 | |
| Relighting | Synthetic Scenes (test) | PSNR22.6288 | 16 | |
| Novel View Synthesis | DTU 15 (test) | PSNR19.11 | 15 | |
| Novel View Synthesis | Synthetic Dataset (test) | PSNR31.0425 | 13 | |
| Novel View Synthesis | Shiny Blender | PSNR26.21 | 13 | |
| Geometry Estimation | StanfordORB | Depth Error1.9 | 11 | |
| Albedo Estimation | Synthetic Dataset (test) | PSNR19.7933 | 10 |