gsplat: An Open-Source Library for Gaussian Splatting
About
gsplat is an open-source library designed for training and developing Gaussian Splatting methods. It features a front-end with Python bindings compatible with the PyTorch library and a back-end with highly optimized CUDA kernels. gsplat offers numerous features that enhance the optimization of Gaussian Splatting models, which include optimization improvements for speed, memory, and convergence times. Experimental results demonstrate that gsplat achieves up to 10% less training time and 4x less memory than the original implementation. Utilized in several research projects, gsplat is actively maintained on GitHub. Source code is available at https://github.com/nerfstudio-project/gsplat under Apache License 2.0. We welcome contributions from the open-source community.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Novel View Synthesis | DL3DV (test) | PSNR24.94 | 120 | |
| Novel View Synthesis | Re10K (test) | PSNR19.234 | 91 | |
| 3D Gaussian Splatting Rendering | Mip-NeRF 360 1080p 1.0 | FPS557 | 64 | |
| 3D Gaussian Splatting Rendering | Mip-NeRF 360 4K 1.0 | FPS167 | 64 | |
| Novel View Synthesis | Mip-NeRF 360 | PSNR29.4 | 44 | |
| Novel View Synthesis | MatrixCity Block Small BEV_2 synthetic | PSNR16.33 | 20 | |
| 3D Scene Reconstruction | Re10K (test) | LPIPS45.7 | 15 | |
| 3D Scene Reconstruction | DL3DV (test) | LPIPS0.412 | 14 | |
| Underwater Image Restoration | D3 | ΔE0020.34 | 13 | |
| Novel View Synthesis | MatrixCity Block Small synthetic (Street) | PSNR22.47 | 10 |