【计算机视觉】Gaussian Splatting源码解读补充（三）_3d gaussian splatting反向传播

• 第一部分
• 第二部分

本文是对学习笔记之——3D Gaussian Splatting源码解读的补充，并订正了一些错误。

五、反向传播

原文第6节：

During the backward pass, we must therefore recover the full sequence of blended points per-pixel in the forward pass. One solution would be to store arbitrarily long lists of blended points per-pixel in global memory [Kopanas et al. 2021]. To avoid the implied dynamic memory management overhead, we instead choose to traverse the per-tile lists again; we can reuse the sorted array of Gaussians and tile ranges from the forward pass. To facilitate gradient computation, we now traverse them back-to-front.

The traversal starts from the last point that affected any pixel in the tile, and loading of points into shared memory again happens collaboratively. Additionally, each pixel will only start (expensive) overlap testing and processing of points if their depth is lower than or equal to the depth of the last point that contributed to its color during the forward pass. Computation of the gradients described in Sec. 4 requires the accumulated opacity values at each step during the original blending process. Rather than trasversing an explicit list of progressively shrinking opacities in the backward pass, we can recover these intermediate opacities by storing only the total accumulated opacity at the end of the forward pass. Specifically, each point stores the final accumulated opacity 声明：本文内容由网友自发贡献，转载请注明出处：【wpsshop】