gsplat: An Open-Source Library for Gaussian Splatting
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866929496019435520 |
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| author | Ye, Vickie Li, Ruilong Kerr, Justin Turkulainen, Matias Yi, Brent Pan, Zhuoyang Seiskari, Otto Ye, Jianbo Hu, Jeffrey Tancik, Matthew Kanazawa, Angjoo |
| author_facet | Ye, Vickie Li, Ruilong Kerr, Justin Turkulainen, Matias Yi, Brent Pan, Zhuoyang Seiskari, Otto Ye, Jianbo Hu, Jeffrey Tancik, Matthew Kanazawa, Angjoo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_06765 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | gsplat: An Open-Source Library for Gaussian Splatting Ye, Vickie Li, Ruilong Kerr, Justin Turkulainen, Matias Yi, Brent Pan, Zhuoyang Seiskari, Otto Ye, Jianbo Hu, Jeffrey Tancik, Matthew Kanazawa, Angjoo Computer Vision and Pattern Recognition 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. |
| title | gsplat: An Open-Source Library for Gaussian Splatting |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2409.06765 |