FLoD：将灵活细节级别集成到3D高斯飞溅中，用于可定制渲染。

FLoD: Integrating Flexible Level of Detail into 3D Gaussian Splatting for Customizable Rendering

August 23, 2024

作者: Yunji Seo, Young Sun Choi, Hyun Seung Son, Youngjung Uh

cs.AI

摘要

3D高斯喷洒（3DGS）通过使用大量小高斯函数实现快速且高质量的渲染，但这也导致了显著的内存消耗。对大量高斯函数的依赖限制了基于3DGS的模型在低成本设备上的应用，因为内存限制。然而，简单地减少高斯函数的数量以适应内存容量较小的设备会导致较低的质量，无法与高端硬件上实现的质量相媲美。为解决这种缺乏可伸缩性的问题，我们提出将灵活细节级别（FLoD）集成到3DGS中，以允许根据硬件能力在不同细节级别上呈现场景。虽然现有的具有细节级别的3DGS侧重于详细重建，但我们的方法提供了使用少量高斯函数进行重建以减少内存需求，以及使用更多高斯函数以获得更多细节。实验证明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约束下进行实时渲染。此外，我们展示了我们的方法适用于不同的3DGS框架，表明其具有整合到未来最先进发展中的潜力。项目页面：https://3dgs-flod.github.io/flod.github.io/

English

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. Project page: https://3dgs-flod.github.io/flod.github.io/