SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality
Fuente:
arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915207741177856 |
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| author | Schiavo, Chiara Camuffo, Elena Badia, Leonardo Milani, Simone |
| author_facet | Schiavo, Chiara Camuffo, Elena Badia, Leonardo Milani, Simone |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16747 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality Schiavo, Chiara Camuffo, Elena Badia, Leonardo Milani, Simone Graphics Computer Vision and Pattern Recognition Multimedia 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. |
| title | SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality |
| topic | Graphics Computer Vision and Pattern Recognition Multimedia |
| url | https://arxiv.org/abs/2503.16747 |