RaRa Clipper: A Clipper for Gaussian Splatting Based on Ray Tracer and Rasterizer
Journal:
arXiv
Published Date:
Jun 25, 2025
Abstract
With the advancement of Gaussian Splatting techniques, a growing number of
datasets based on this representation have been developed. However, performing
accurate and efficient clipping for Gaussian Splatting remains a challenging
and unresolved problem, primarily due to the volumetric nature of Gaussian
primitives, which makes hard clipping incapable of precisely localizing their
pixel-level contributions. In this paper, we propose a hybrid rendering
framework that combines rasterization and ray tracing to achieve efficient and
high-fidelity clipping of Gaussian Splatting data. At the core of our method is
the RaRa strategy, which first leverages rasterization to quickly identify
Gaussians intersected by the clipping plane, followed by ray tracing to compute
attenuation weights based on their partial occlusion. These weights are then
used to accurately estimate each Gaussian's contribution to the final image,
enabling smooth and continuous clipping effects. We validate our approach on
diverse datasets, including general Gaussians, hair strand Gaussians, and
multi-layer Gaussians, and conduct user studies to evaluate both perceptual
quality and quantitative performance. Experimental results demonstrate that our
method delivers visually superior results while maintaining real-time rendering
performance and preserving high fidelity in the unclipped regions.
