In production rendering systems, caustics are typically rendered via photon mapping and gathering, a process often hindered by insufficient photon density. In this paper, we propose a novel photon guiding method to improve the photon density and overall quality for caustic rendering. The key insight of our approach is the application of a global 3D Gaussian mixture model, used in conjunction with an adaptive light sampler. This combination effectively guides photon emission in expansive 3D scenes with multiple light sources. By employing a global 3D Gaussian mixture, our method precisely models the distribution of the points of interest. To sample emission directions from the distribution at any observation point, we introduce a novel directional transform of the 3D Gaussian, which ensures accurate photon emission guiding. Furthermore, our method integrates a global light cluster tree, which models the contribution distribution of light sources to the image, facilitating effective light source selection. We conduct experiments demonstrating that our approach robustly outperforms existing photon guiding techniques across a variety of scenarios, significantly advancing the quality of caustic rendering.

翻译：在工业级渲染系统中，焦散效应通常通过光子映射与收集实现，但这一过程常受限于光子密度不足。本文提出一种新型光子引导方法，旨在提升焦散渲染中的光子密度与整体质量。该方法的核心创新在于将全局三维高斯混合模型与自适应光源采样器相结合，能够有效引导多光源大尺度三维场景中的光子发射。通过采用全局三维高斯混合模型，本方法精确建模了兴趣点的空间分布。为从观测点分布的发射方向进行采样，我们引入了一种新颖的三维高斯方向变换技术，确保光子发射引导的准确性。此外，本方法集成了全局光源聚类树结构，该结构可建模光源对图像贡献的分布特性，从而有效支持光源选择。实验结果表明，本方法在多种场景下均显著优于现有光子引导技术，大幅提升了焦散渲染质量。