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/.

翻译：我们提出了通用Beta泼溅（UBS），这是一个将3D高斯泼溅推广至N维各向异性Beta核的统一框架，用于显式辐射场渲染。与固定的高斯基元不同，Beta核能够在单一表示内实现跨空间、角度和时间维度的可控依赖关系建模。我们的统一方法能够捕捉复杂的光线传输效应，处理各向异性的视角相关外观，并对场景动态进行建模，而无需辅助网络或特定的颜色编码。UBS通过将高斯泼溅近似为其特例来保持向后兼容性，从而保证了即插即用的可用性和较低的性能下限。学习到的Beta参数能够自然地将场景属性分解为可解释的组成部分，而无需显式监督：空间（表面与纹理）、角度（漫反射与镜面反射）以及时间（静态与动态）。我们基于CUDA加速的实现实现了实时渲染，同时在静态、视角相关和动态基准测试中持续优于现有方法，确立了Beta核作为一种可扩展的通用基元用于辐射场渲染。我们的项目网站位于 https://rongliu-leo.github.io/universal-beta-splatting/。