Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing
About
In this paper, we present a novel differentiable point-based rendering framework to achieve photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla 3D Gaussians by associating extra properties, including normal vectors, BRDF parameters, and incident lighting from various directions. From a collection of multi-view images, the 3D scene is optimized through 3D Gaussian Splatting while BRDF and lighting are decomposed by physically based differentiable rendering. To produce plausible shadow effects in photo-realistic relighting, we introduce an innovative point-based ray tracing with the bounding volume hierarchies for efficient visibility pre-computation. Extensive experiments demonstrate our improved BRDF estimation, novel view synthesis and relighting results compared to state-of-the-art approaches. The proposed framework showcases the potential to revolutionize the mesh-based graphics pipeline with a point-based pipeline enabling editing, tracing, and relighting.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Novel View Synthesis | DTU | PSNR31.82 | 115 | |
| Novel View Synthesis | RelightObj NVS (test) | PSNR (bridge)30.61 | 13 | |
| Relighting | RelightObj (Unseen Relights) | PSNR (night)23.91 | 13 | |
| Relighting | RelightObj (Seen Relights) | PSNR (bridge)22.32 | 13 | |
| Novel View Synthesis | FIPT synthetic dataset | PSNR18.85 | 11 | |
| Shape Reconstruction | RMVP3D | MAE (SHISA)16.69 | 11 | |
| Shape Reconstruction | PISR | MAE (L-RABBIT)29.19 | 11 | |
| Roughness Estimation | Synthetic dataset | MSE0.013 | 10 | |
| Novel View Synthesis | TensoIR Synthetic | PSNR33.35 | 10 | |
| Novel View Synthesis | MipNeRF | PSNR18.61 | 10 |