Simulating the light transport of volumetric effects poses significant challenges and costs, especially in the presence of heterogeneous volumes. Generating stochastic paths for volume rendering involves multiple decisions, and previous works mainly focused on directional and distance sampling, where the volume scattering probability (VSP), i.e., the probability of scattering inside a volume, is indirectly determined as a byproduct of distance sampling. We demonstrate that direct control over the VSP can significantly improve efficiency and present an unbiased volume rendering algorithm based on an existing resampling framework for precise control over the VSP. Compared to previous state-of-the-art, which can only increase the VSP without guaranteeing to reach the desired value, our method also supports decreasing the VSP. We further present a data-driven guiding framework to efficiently learn and query an approximation of the optimal VSP everywhere in the scene without the need for user control. Our approach can easily be combined with existing path-guiding methods for directional sampling at minimal overhead and shows significant improvements over the state-of-the-art in various complex volumetric lighting scenarios.

中文翻译：

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体积散射概率引导


模拟体积效应的光传输带来了巨大的挑战和成本，尤其是在存在异质体积的情况下。为体积渲染生成随机路径涉及多个决策，以前的工作主要集中在定向和距离采样，其中体积散射概率 （VSP），即体积内部散射的概率，间接确定为距离采样的副产品。我们证明，对 VSP 的直接控制可以显着提高效率，并提出了一种基于现有重采样框架的无偏体积渲染算法，用于精确控制 VSP。与以前只能增加 VSP 而不能保证达到所需值的最新方法相比，我们的方法还支持降低 VSP。我们进一步提出了一个数据驱动的指导框架，可以在场景中的任何地方有效地学习和查询最佳 VSP 的近似值，而无需用户控制。我们的方法可以轻松地与现有的路径引导方法相结合，以最小的开销进行定向采样，并在各种复杂的体积照明场景中显示出对最先进的技术的显着改进。