PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting

Understand

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy.

• 3D Gaussian Splatting (3D-GS), a foundational point-based parametric 3D scene representation, models scenes as large sets of 3D Gaussians.
• However, complex scenes can consist of millions of Gaussians, resulting in high storage and memory requirements that limit the viability of 3D-GS on devices with limited resources.
• Current techniques for compressing these pretrained models by pruning Gaussians rely on combining heuristics to determine which Gaussians to remove.