  3D Gaussian Splatting (3DGS) has made a significant stride in novel view
synthesis, demonstrating top-notch rendering quality while achieving real-time
rendering speed. However, the excessively large number of Gaussian primitives
resulting from 3DGS' suboptimal densification process poses a major challenge,
slowing down frame-per-second (FPS) and demanding considerable memory cost,
making it unfavorable for low-end devices. To cope with this issue, many
follow-up studies have suggested various pruning techniques, often in
combination with different score functions, to optimize rendering performance.
Nonetheless, a comprehensive discussion regarding their effectiveness and
implications across all techniques is missing. In this paper, we first
categorize 3DGS pruning techniques into two types: Cross-view pruning and
pixel-wise pruning, which differ in their approaches to rank primitives. Our
subsequent experiments reveal that while cross-view pruning leads to disastrous
quality drops under extreme Gaussian primitives decimation, the pixel-wise
pruning technique not only sustains relatively high rendering quality with
minuscule performance degradation but also provides a reasonable minimum
boundary for pruning. Building on this observation, we further propose multiple
variations of score functions and empirically discover that the color-weighted
score function outperforms others for discriminating insignificant primitives
for rendering. We believe our research provides valuable insights for
optimizing 3DGS pruning strategies for future works.
