Mathematical Supplement for the $\texttt{gsplat}$ Library

4 Dec 2023  ·  Vickie Ye, Angjoo Kanazawa ·

This report provides the mathematical details of the gsplat library, a modular toolbox for efficient differentiable Gaussian splatting, as proposed by Kerbl et al. It provides a self-contained reference for the computations involved in the forward and backward passes of differentiable Gaussian splatting. To facilitate practical usage and development, we provide a user friendly Python API that exposes each component of the forward and backward passes in rasterization at .

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