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重要模型。然而，三维高斯泼溅渲染流程的效率依赖于若干简化操作。值得注意的是，将高斯分布简化为具有单一视角空间深度的二维泼溅会在视角旋转时引入突现和混合伪影。解决此问题需要精确的逐像素深度计算，但与全局排序操作相比，完整的逐像素排序被证明成本过高。本文提出一种新颖的分层光栅化方法，以最小的处理开销系统地对泼溅进行重新排序与剔除。我们的软件光栅化器有效消除了突现伪影和视角不一致性，定量与定性测量均验证了此效果。同时，我们的方法抑制了通过突现伪影实现视角依赖效应作弊的可能性，从而确保更真实的表示。尽管杜绝了作弊行为，我们的方法在测试图像上仍获得了可比的定量结果，同时提升了运动中新视角合成的一致性。得益于其设计，我们的分层方法平均仅比原始高斯泼溅慢4%。值得注意的是，强制一致性使得高斯分布数量可减少约一半，同时保持近乎相同的质量和视角一致性。因此，渲染性能提升近一倍，使我们的方法比原始高斯泼溅快1.6倍，且内存需求降低50%。