3D Gaussian Splatting (3DGS) is a recent explicit 3D representation that has achieved high-quality reconstruction and real-time rendering of complex scenes. However, the rasterization pipeline still suffers from unnecessary overhead resulting from avoidable serial Gaussian culling, and uneven load due to the distinct number of Gaussian to be rendered across pixels, which hinders wider promotion and application of 3DGS. In order to accelerate Gaussian splatting, we propose AdR-Gaussian, which moves part of serial culling in Render stage into the earlier Preprocess stage to enable parallel culling, employing adaptive radius to narrow the rendering pixel range for each Gaussian, and introduces a load balancing method to minimize thread waiting time during the pixel-parallel rendering. Our contributions are threefold, achieving a rendering speed of 310% while maintaining equivalent or even better quality than the state-of-the-art. Firstly, we propose to early cull Gaussian-Tile pairs of low splatting opacity based on an adaptive radius in the Gaussian-parallel Preprocess stage, which reduces the number of affected tile through the Gaussian bounding circle, thus reducing unnecessary overhead and achieving faster rendering speed. Secondly, we further propose early culling based on axis-aligned bounding box for Gaussian splatting, which achieves a more significant reduction in ineffective expenses by accurately calculating the Gaussian size in the 2D directions. Thirdly, we propose a balancing algorithm for pixel thread load, which compresses the information of heavy-load pixels to reduce thread waiting time, and enhance information of light-load pixels to hedge against rendering quality loss. Experiments on three datasets demonstrate that our algorithm can significantly improve the Gaussian Splatting rendering speed.
3D 高斯投影（3D Gaussian Splatting, 3DGS）是一种近期提出的显式 3D 表示方法，已在复杂场景的高质量重建和实时渲染中取得了显著成果。然而，栅格化管线仍然存在由于可避免的串行高斯剔除导致的不必要开销，以及每个像素渲染的高斯数量不同带来的负载不均，这阻碍了 3DGS 的更广泛推广与应用。为了加速高斯投影，我们提出了 AdR-Gaussian 方法，将渲染阶段的部分串行剔除提前至预处理阶段，实现并行剔除，并通过自适应半径缩小每个高斯的渲染像素范围，同时引入负载平衡方法，以最小化像素并行渲染时线程的等待时间。我们的贡献主要有三点，使渲染速度提升了 310%，同时保持了与现有最先进方法相当甚至更高的质量。 首先，我们在高斯并行预处理阶段中，基于自适应半径对低投影不透明度的高斯-瓦片对进行早期剔除，减少通过高斯包围圆影响的瓦片数量，从而减少不必要的开销并加快渲染速度。其次，我们进一步提出基于轴对齐包围盒的高斯投影早期剔除，通过精确计算高斯在二维方向的大小，实现了更大幅度的无效开销减少。第三，我们提出了一个像素线程负载平衡算法，通过压缩高负载像素的信息来减少线程等待时间，并增强轻负载像素的信息，以对冲渲染质量的损失。三个数据集上的实验表明，我们的算法可以显著提升高斯投影的渲染速度。