Despite significant advances in algorithms and hardware, global illumination continues to be a challenge in the real-time domain. Time constraints often force developers to either compromise on the quality of global illumination or disregard it altogether. We take advantage of a common setup in modern games: having a set of a level, which is a static scene with dynamic characters and lighting. We introduce a novel method for efficiently and accurately rendering global illumination in dynamic scenes. Our hybrid technique leverages precomputation and neural networks to capture the light transport of a static scene. Then, we introduce a method to compute the difference between the current scene and the static scene, which we already precomputed. By handling the bulk of the light transport through precomputation, our method only requires the rendering of a minimal difference, reducing the noise and increasing the quality.

翻译：尽管算法与硬件取得了显著进展，全局光照在实时渲染领域仍是挑战。时间限制常迫使开发者要么牺牲全局光照质量，要么完全忽略它。我们利用现代游戏中常见的设置：拥有包含动态角色与照明的静态场景关卡。本文提出一种在动态场景中高效、精确渲染全局光照的新方法。我们的混合技术通过预计算与神经网络捕获静态场景的光传输特性，随后引入一种方法计算当前场景与已预计算的静态场景之间的差异。由于通过预计算处理了大部分光传输，本方法仅需渲染最小差异，从而降低噪点并提升质量。