Temporally Reliable Motion Vectors for Real-time Ray Tracing
Temporally Reliable Motion Vectors for Real-time Ray Tracing
复制标题
用于实时光线追踪的时间可靠的运动矢量
DOI：
10.1111/cgf.142616
复制
发表时间：
2021
影响因子：
2.5
通讯作者：
Yan Ling-Qi
中科院分区：
文献类型：
--
作者：
Zeng Zheng;Liu Shiqiu;Yang Jinglei;Wang Lu;Yan Ling-Qi
实时光线追踪（RTRT）正在得到普遍应用。 RTRT 的关键是一种可靠的去噪方案，该方案可以从明显欠采样的噪声输入中重建干净的图像，由于当前硬件计算能力的限制，通常每像素 1 个样本。最先进的重建方法都依赖于时间滤波来查找前一帧中当前像素的对应关系，使用每像素屏幕空间运动向量进行描述。虽然这些方法被证明很强大，但它们存在一个常见问题，即当运动向量无效时，即当时间对应性不明显可用或理论上不存在时，时间信息无法使用。我们引入时间可靠的运动向量，旨在更深入地探索时间相干性，特别是对于阴影、光泽反射和遮挡等普遍认为困难的应用，其关键思想是检测和跟踪每种效果的原因。我们表明，与最先进的方法相比，我们的时间可靠的运动向量在各种动态场景上产生了明显更好的时间结果，但性能开销可以忽略不计。
Real‐time ray tracing (RTRT) is being pervasively applied. The key to RTRT is a reliable denoising scheme that reconstructs clean images from significantly undersampled noisy inputs, usually at 1 sample per pixel as limited by current hardware's computing power. The state of the art reconstruction methods all rely on temporal filtering to find correspondences of current pixels in the previous frame, described using per‐pixel screen‐space motion vectors. While these approaches are demonstrated powerful, they suffer from a common issue that the temporal information cannot be used when the motion vectors are not valid, i.e. when temporal correspondences are not obviously available or do not exist in theory.We introduce temporally reliable motion vectors that aim at deeper exploration of temporal coherence, especially for the generally‐believed difficult applications on shadows, glossy reflections and occlusions, with the key idea to detect and track the cause of each effect. We show that our temporally reliable motion vectors produce significantly better temporal results on a variety of dynamic scenes when compared to the state of the art methods, but with negligible performance overhead.