3D Gaussian Splatting (3DGS) achieves fast and high-quality renderings by using numerous small Gaussians, which leads to significant memory consumption. This reliance on a large number of Gaussians restricts the application of 3DGS-based models on low-cost devices due to memory limitations. However, simply reducing the number of Gaussians to accommodate devices with less memory capacity leads to inferior quality compared to the quality that can be achieved on high-end hardware. To address this lack of scalability, we propose integrating a Flexible Level of Detail (FLoD) to 3DGS, to allow a scene to be rendered at varying levels of detail according to hardware capabilities. While existing 3DGSs with LoD focus on detailed reconstruction, our method provides reconstructions using a small number of Gaussians for reduced memory requirements, and a larger number of Gaussians for greater detail. Experiments demonstrate our various rendering options with tradeoffs between rendering quality and memory usage, thereby allowing real-time rendering across different memory constraints. Furthermore, we show that our method generalizes to different 3DGS frameworks, indicating its potential for integration into future state-of-the-art developments.
3D 高斯点云（3DGS）通过使用大量小型高斯实现了快速和高质量的渲染，但这也导致了显著的内存消耗。这种对大量高斯的依赖限制了 3DGS 基础模型在低成本设备上的应用，因为这些设备的内存有限。然而，简单地减少高斯数量以适应内存较小的设备，会导致比高端硬件上实现的质量差。为了解决这种可扩展性不足的问题，我们提出将灵活细节级别（FLoD）集成到 3DGS 中，以根据硬件能力以不同细节级别渲染场景。虽然现有的带有细节级别的 3DGS 侧重于详细重建，我们的方法使用少量高斯进行重建以减少内存需求，并使用更多高斯以获得更高细节。实验展示了我们的各种渲染选项在渲染质量和内存使用之间的权衡，从而允许在不同内存限制下进行实时渲染。此外，我们还表明我们的方法可以推广到不同的 3DGS 框架，显示出其在未来前沿发展中的整合潜力。