FLoD：將靈活的細節層級整合到 3D 高斯飛濺中，以供自定義渲染。

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 高斯點陣化（3DGS）通過使用眾多小高斯函數實現快速且高質量的渲染，但這導致了顯著的內存消耗。對大量高斯函數的依賴限制了基於 3DGS 的模型在低成本設備上的應用，因為內存限制。然而，簡單地減少高斯函數的數量以適應內存容量較小的設備，會導致較低的質量，無法與高端硬件實現的質量相比。為解決這種缺乏可擴展性的問題，我們提出將靈活細節層級（FLoD）集成到 3DGS 中，以允許根據硬件能力在不同細節層級上呈現場景。現有的具有細節層級的 3DGS 主要關注詳細的重建，而我們的方法則使用少量高斯函數進行重建，以降低內存需求，並使用更多高斯函數以獲得更多細節。實驗證明了我們的各種渲染選項在渲染質量和內存使用之間的權衡，從而實現了在不同內存限制下的實時渲染。此外，我們展示了我們的方法對不同的 3DGS 框架具有泛化能力，表明其潛力可以整合到未來最先進的發展中。項目頁面：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/