Gaussian Splatting has emerged as a prominent model for constructing 3D representations from images across diverse domains. However, the efficiency of the 3D Gaussian Splatting rendering pipeline relies on several simplifications. Notably, reducing Gaussian to 2D splats with a single view-space depth introduces popping and blending artifacts during view rotation. Addressing this issue requires accurate per-pixel depth computation, yet a full per-pixel sort proves excessively costly compared to a global sort operation. In this paper, we present a novel hierarchical rasterization approach that systematically resorts and culls splats with minimal processing overhead. Our software rasterizer effectively eliminates popping artifacts and view inconsistencies, as demonstrated through both quantitative and qualitative measurements. Simultaneously, our method mitigates the potential for cheating view-dependent effects with popping, ensuring a more authentic representation. Despite the elimination of cheating, our approach achieves comparable quantitative results for test images, while increasing the consistency for novel view synthesis in motion. Due to its design, our hierarchical approach is only 4% slower on average than the original Gaussian Splatting. Notably, enforcing consistency enables a reduction in the number of Gaussians by approximately half with nearly identical quality and view-consistency. Consequently, rendering performance is nearly doubled, making our approach 1.6x faster than the original Gaussian Splatting, with a 50% reduction in memory requirements.

翻译：高斯泼溅已成为从不同领域图像构建三维表示的主流模型。然而，三维高斯泼溅渲染管线的效率依赖于若干简化处理。值得注意的是，将高斯体简化为具有单一视图空间深度的二维溅射会在视角旋转时产生跳跃伪影和混合伪影。解决该问题需要精确的逐像素深度计算，但相较于全局排序操作，完整的逐像素排序成本过高。本文提出一种新颖的层次化光栅化方法，能以最小处理开销系统性地对溅射进行重排序与剔除。通过定量与定性测量验证，我们的软件光栅器有效消除了跳跃伪影与视角不一致性。同时，该方法抑制了利用跳跃伪影作弊的视角相关效果，确保更真实的场景表达。尽管消除了作弊行为，本方法在测试图像上仍能获得可比的定量结果，同时增强了运动状态下新视图合成的连贯性。受设计特性影响，层次化方法平均仅比原始高斯泼溅慢4%。值得注意的是，强制一致性约束可使高斯体数量减少约一半，同时保持近乎相同的质量与视角一致性。因此，渲染性能近乎翻倍，本方法比原始高斯泼溅快1.6倍，内存需求降低50%。