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.
gsplat 是一个开源库，专为训练和开发 Gaussian Splatting 方法设计。它包含与 PyTorch 库兼容的 Python 绑定前端和高度优化的 CUDA 内核后端。gsplat 提供了多种功能，提升了 Gaussian Splatting 模型的优化效果，包括在速度、内存和收敛时间方面的优化改进。实验结果表明，gsplat 的训练时间比原始实现减少了多达10%，内存消耗减少了4倍。gsplat 已被多个研究项目使用，并在 GitHub 上积极维护。