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.

翻译：三维高斯溅射（3DGS）是一种新兴的显式三维表示方法，已在复杂场景的高质量重建与实时渲染方面取得显著成果。然而，其光栅化流水线仍存在两个关键瓶颈：一是由可避免的串行高斯剔除所导致的不必要开销，二是由于各像素待渲染高斯数量不均造成的负载不均衡，这些问题阻碍了3DGS的更广泛推广与应用。为加速高斯溅射过程，本文提出AdR-Gaussian方法，通过以下三项创新实现310%的渲染速度提升，同时保持与现有最优方法相当甚至更优的质量：首先，将渲染阶段的部分串行剔除提前至预处理阶段实现并行化，并采用自适应半径缩小各高斯的渲染像素范围；其次，引入负载均衡机制以最小化像素并行渲染时的线程等待时间。具体贡献包括：第一，在并行高斯处理的预处理阶段，基于自适应半径对低溅射不透明度的高斯-图块对进行早期剔除，通过高斯边界圆减少受影响图块数量，从而降低冗余开销并提升渲染速度；第二，进一步提出基于轴对齐包围盒的高斯溅射早期剔除方法，通过精确计算二维方向上的高斯尺寸，实现无效开销的更显著削减；第三，设计像素线程负载均衡算法，通过压缩高负载像素信息减少线程等待时间，同时增强低负载像素信息以对冲渲染质量损失。在三个数据集上的实验表明，本算法能显著提升高斯溅射的渲染速度。