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：本文提出通用Beta溅射（UBS）框架，该统一框架将3D高斯溅射推广至N维各向异性Beta核，用于显式辐射场渲染。与固定的高斯基元不同，Beta核能够在单一表征内实现跨空间、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，并建模场景动态，无需依赖辅助网络或特定颜色编码。UBS通过将高斯溅射作为特例进行近似，保持了向后兼容性，从而确保即插即用特性和性能下界保障。学习得到的Beta参数能够自然地将场景属性解耦为可解释的分量而无需显式监督：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超越现有方法，确立了Beta核作为辐射场渲染的可扩展通用基元。项目网站详见 https://rongliu-leo.github.io/universal-beta-splatting/。