StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time
  Rendering
Lukas Radl Michael Steiner Mathias Parger Alexander Weinrauch Bernhard Kerbl Markus Steinberger
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.