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.

翻译：三维高斯泼溅（3DGS）在从机器人技术到扩展现实（XR）的多种应用中，显著提升了三维场景可视化的效率与真实感。本文提出SAGE（扩展现实中语义驱动的自适应高斯泼溅），这是一种新颖的框架，旨在通过动态调整经语义分割识别的不同3DGS对象的细节层次（LOD）来增强用户体验。实验结果表明，SAGE在保持期望目标视觉质量的同时，有效降低了内存与计算开销，从而为交互式XR应用提供了有力的优化方案。