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arXiv · 2503.16747

SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality

Chiara Schiavo·Elena Camuffo·Leonardo Badia·Simone Milani
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Abstract

3D Gaussian Splatting (3DGS) has significantly improved the efficiency and realism of three-dimensional scene visualization in several applications, ranging from robotics to eXtended Reality (XR). This work presents SAGE (Semantic-Driven Adaptive Gaussian Splatting in Extended Reality), a novel framework designed to enhance the user experience by dynamically adapting the Level of Detail (LOD) of different 3DGS objects identified via a semantic segmentation. Experimental results demonstrate how SAGE effectively reduces memory and computational overhead while keeping a desired target visual quality, thus providing a powerful optimization for interactive XR applications.

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Chiara Schiavo, Elena Camuffo, Leonardo Badia, Simone Milani. 2025-03-20. SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality. https://arxiv.org/abs/2503.16747

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