发表机构
Peking University; Central Media Technology Institution, Huawei（北京大学; 华为中央媒体技术研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对实时渲染中光线追踪AO和阴影存在噪声及成本高的问题，提出遮挡点重用框架，通过将估计器转换为遮挡器域积分，结合MIS公式，推导无偏和有偏估计器，实验验证该方法能提升AO和阴影质量。
AI 中文摘要
环境光遮蔽（AO）和软阴影是实时渲染中空间感知的关键可见性线索。硬件光线追踪提供了评估这些效果的直接方法，实现了光线追踪AO和区域光阴影，避免了屏幕空间AO和阴影映射的许多限制。然而，实时预算限制每个像素只能发射少量光线，使得原始光线追踪估计有噪声且成本高。我们提出了一个遮挡点重用框架，在首次命中遮挡点的域中重用追踪样本，而不是直接重用最终着色值或光照样本。这为AO提供了光线重用公式，而不仅仅是过滤或重用已完成的AO值。关键思想是将AO和区域光阴影估计器转换为遮挡器域积分，然后用多重重要性采样（MIS）公式组合相邻的遮挡器样本。对于AO和阴影，我们推导了无偏估计器以验证向转换积分的收敛，以及为实际实时执行设计的有偏估计器。有偏变体假设局部首次命中遮挡器一致性；对于阴影，这种基于遮挡器的假设比重用光照样本时常用的可见性一致性假设更能匹配局部可见性几何。实验表明，与非重用光线追踪基线相比，AO和阴影质量更高，且在可比成本下阴影质量优于光照样本重用。
英文摘要
Ambient occlusion (AO) and soft shadows are critical visibility cues for spatial perception in real-time rendering. Hardware ray tracing provides a direct way to evaluate these effects, enabling ray-traced AO and area-light shadows that avoid many limitations of screen-space AO and shadow mapping. However, real-time budgets allow only a few rays per pixel, leaving raw ray-traced estimates noisy and expensive. We present an occlusion-point reuse framework that reuses traced samples in the domain of first-hit occlusion points instead of directly reusing final shading values or light samples. This provides a ray-reuse formulation for AO, rather than merely filtering or reusing completed AO values. The key idea is to transform AO and area-light shadow estimators into occluder-domain integrals, then combine neighboring occluder samples with a multiple-importance-sampling (MIS) formulation. For both AO and shadows, we derive unbiased estimators that validate convergence to the transformed integrals, as well as biased estimators designed for practical real-time execution. The biased variants assume local first-hit occluder consistency; for shadows, this occluder-based assumption better matches local visibility geometry than the visibility-consistency assumption commonly used when reusing light samples. Experiments show higher AO and shadow quality than non-reuse ray-traced baselines, and better shadow quality than light-sample reuse at comparable cost.
