title: FLoD: Integrating Flexible Level of Detail into 3D Gaussian Splatting
    for Customizable Rendering
summary: 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/
paper_authors._id: 66cbf9d8d20991c2a0123ce9
paper_authors.name: Yunji Seo
paper_authors._id: 66cbf9d8d20991c2a0123cea
paper_authors.name: Young Sun Choi
paper_authors._id: 66cbf9d8d20991c2a0123ceb
paper_authors.name: Hyun Seung Son
paper_authors._id: 66cbf9d8d20991c2a0123cec
paper_authors.name: Youngjung Uh
paper_title: FLoD: Integrating Flexible Level of Detail into 3D Gaussian Splatting
    for Customizable Rendering
paper_summary: 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/