RaRa Clipper: A Clipper for Gaussian Splatting Based on Ray Tracer and Rasterizer
Da Li, Donggang Jia, Yousef Rajeh, Dominik Engel, Ivan Viola

TL;DR
RaRa Clipper introduces a hybrid rasterization and ray tracing framework for precise, efficient Gaussian Splatting clipping, enabling high-fidelity, real-time rendering across diverse datasets.
Contribution
The paper presents a novel hybrid rendering approach combining rasterization and ray tracing for accurate Gaussian Splatting clipping, addressing volumetric challenges.
Findings
Achieves high-quality, smooth clipping effects.
Maintains real-time rendering performance.
Works effectively on various Gaussian datasets.
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…
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Taxonomy
TopicsIoT Networks and Protocols
