Research on differentiable scene representations is consistently moving towards more efficient, real-time models. Recently, this has led to the popularization of splatting methods, which eschew the traditional ray-based rendering of radiance fields in favor of rasterization. This has yielded a significant improvement in rendering speeds due to the efficiency of rasterization algorithms and hardware, but has come at a cost: the approximations that make rasterization efficient also make implementation of light transport phenomena like reflection and refraction much more difficult. We propose a novel scene representation which avoids these approximations, but keeps the efficiency and reconstruction quality of splatting by leveraging a decades-old efficient volumetric mesh ray tracing algorithm which has been largely overlooked in recent computer vision research. The resulting model, which we name Radiant Foam, achieves rendering speed and quality comparable to Gaussian Splatting, without the constraints of rasterization. Unlike ray traced Gaussian models that use hardware ray tracing acceleration, our method requires no special hardware or APIs beyond the standard features of a programmable GPU.
可微场景表示的研究始终朝着更高效、实时的模型发展。最近，这推动了点云方法的普及，这些方法摒弃了传统的基于光线的辐射场渲染，而采用光栅化渲染。由于光栅化算法和硬件的高效性，这在渲染速度上取得了显著提高，但也带来了代价：使光栅化高效的近似方法也使得光传输现象（如反射和折射）的实现变得更加困难。我们提出了一种新型的场景表示方法，避免了这些近似，但通过利用一种已经被计算机视觉研究大多忽视的几十年历史的高效体积网格光线追踪算法，保留了点云方法的效率和重建质量。我们命名这种模型为Radiant Foam，它在渲染速度和质量上与高斯点云（Gaussian Splatting）相当，但没有光栅化的约束。与使用硬件光线追踪加速的光线追踪高斯模型不同，我们的方法不需要特殊硬件或API，仅依赖于可编程GPU的标准功能。