FLoD: Integrating Flexible Level of Detail into 3D Gaussian Splatting
  for Customizable Rendering
Authors: name: Yunji Seo, name: Young Sun Choi, name: Hyun Seung Son, name: Youngjung Uh

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/