Generalized non-exponential Gaussian splatting

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Authors: Sébastien Speierer, Adrián Jarabo
Cited by: 0
References: 9

Abstract

In this work we generalize 3D Gaussian splatting (3DGS) to a wider family of physically-based alpha-blending operators. 3DGS has become the standard de-facto for radiance field rendering and reconstruction, given its flexibility and efficiency. At its core, it is based on alpha-blending sorted semitransparent primitives, which in the limit converges to the classic radiative transfer function with exponential transmittance. Inspired by recent research on non-exponential radiative transfer, we generalize the image formation model of 3DGS to non-exponential regimes. Based on this generalization, we use a quadratic transmittance to define sub-linear, linear, and super-linear versions of 3DGS, which exhibit faster-than-exponential decay. We demonstrate that these new non-exponential variants achieve similar quality than the original 3DGS but significantly reduce the number of overdraws, which result on speed-ups of up to $4\times$ in complex real-world captures, on a ray-tracing-based renderer.

Fields of Study & Subjects

Computer Graphics and Visualization Techniques 3D Shape Modeling and Analysis Advanced Vision and Imaging

Publication details

Journal / source
arXiv (Cornell University)
Publication date
3 March 2026
Language
EN
Document type
Preprint