MeshSplatting: Differentiable Rendering with Opaque Meshes
About
Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain incompatible with mesh-based pipelines that power AR/VR and game engines. We present MeshSplatting, a mesh-based reconstruction approach that jointly optimizes geometry and appearance through differentiable rendering. By enforcing connectivity via restricted Delaunay triangulation and refining surface consistency, MeshSplatting creates end-to-end smooth, visually high-quality meshes that render efficiently in real-time 3D engines. On Mip-NeRF360, it boosts PSNR by +0.69 dB over the current state-of-the-art MiLo for mesh-based novel view synthesis, while training 2x faster and using 2x less memory, bridging neural rendering and interactive 3D graphics for seamless real-time scene interaction. The project page is available at https://meshsplatting.github.io/.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Novel View Synthesis | Mip-NeRF360 | PSNR24.78 | 104 | |
| Novel View Synthesis | Mip-NeRF360 (test) | -- | 58 | |
| 3D Reconstruction | DTU | Average Error0.79 | 32 | |
| Appearance Rendering | FAST-LIVO2 | PSNR25.78 | 11 | |
| Appearance Rendering | ScanNet V2 | PSNR25.64 | 8 | |
| Appearance Rendering | ScanNet++ | PSNR27.71 | 8 | |
| Novel View Synthesis | Tanks&Temples | PSNR20.52 | 8 | |
| Appearance Rendering | VR-NeRF | PSNR25.23 | 8 | |
| Appearance Rendering | KITTI | PSNR17.35 | 8 | |
| Appearance Rendering | Waymo | PSNR23.1 | 8 |