Universal Beta Splatting
This work addresses the need for a unified, scalable primitive for radiance field rendering, offering improvements in capturing complex light transport and scene dynamics without auxiliary networks, though it builds incrementally on Gaussian Splatting.
The paper tackles the problem of explicit radiance field rendering by introducing Universal Beta Splatting, a framework that generalizes 3D Gaussian Splatting to N-dimensional anisotropic Beta kernels, enabling real-time rendering and outperforming existing methods across static, view-dependent, and dynamic benchmarks.
We introduce Universal Beta Splatting (UBS), a unified framework that generalizes 3D Gaussian Splatting to N-dimensional anisotropic Beta kernels for explicit radiance field rendering. Unlike fixed Gaussian primitives, Beta kernels enable controllable dependency modeling across spatial, angular, and temporal dimensions within a single representation. Our unified approach captures complex light transport effects, handles anisotropic view-dependent appearance, and models scene dynamics without requiring auxiliary networks or specific color encodings. UBS maintains backward compatibility by approximating to Gaussian Splatting as a special case, guaranteeing plug-in usability and lower performance bounds. The learned Beta parameters naturally decompose scene properties into interpretable without explicit supervision: spatial (surface vs. texture), angular (diffuse vs. specular), and temporal (static vs. dynamic). Our CUDA-accelerated implementation achieves real-time rendering while consistently outperforming existing methods across static, view-dependent, and dynamic benchmarks, establishing Beta kernels as a scalable universal primitive for radiance field rendering. Our project website is available at https://rongliu-leo.github.io/universal-beta-splatting/.