让3D高斯点云逐步渲染,先看重点内容,省内存省带宽。
PRoGS: Progressive Rendering of Gaussian Splats
- 按重要性排序高斯点,逐步加载渲染,先呈现关键视觉内容。
- 结合压缩技术后,传输量减少,渲染质量显著优于现有方法。
- 适合移动端、流媒体等内存或带宽受限的场景使用。
过去一年,3D高斯点云(3DGS)因其在视觉上的精确表现受到广泛关注。然而,其存储开销大,每个点需独立存储。尽管压缩技术可降低内存占用,但仍需加载整个场景才能开始渲染。本文提出一种新型渐进式渲染方法,旨在尽早呈现接近最终效果的可见内容,无需将全部场景载入内存。该方法通过估算每个高斯点对最终图像的贡献,建立优先级顺序,指导渲染过程。此外,我们证明该方法可与现有压缩技术结合,实现3DGS场景的渐进式渲染与流式传输,聚焦于最重要点以优化带宽使用。整体上,本工作为远程托管的3DGS内容在流媒体场景中更快地提供给终端用户奠定了基础,实验表明,在所有指标上均显著优于现有方法。
原文摘要 · Abstract (English)
Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's individual data must be stored. While compression techniques offer a potential solution by reducing the memory footprint, they still necessitate retrieving the entire scene before any part of it can be rendered. In this work, we introduce a novel approach for progressively rendering such scenes, aiming to display visible content that closely approximates the final scene as early as possible without loading the entire scene into memory. This approach benefits both on-device rendering applications limited by memory constraints and streaming applications where minimal bandwidth usage is preferred. To achieve this, we approximate the contribution of each Gaussian to the final scene and construct an order of prioritization on their inclusion in the rendering process. Additionally, we demonstrate that our approach can be combined with existing compression methods to progressively render (and stream) 3DGS scenes, optimizing bandwidth usage by focusing on the most important splats within a scene. Overall, our work establishes a foundation for making remotely hosted 3DGS content more quickly accessible to end-users in over-the-top consumption scenarios, with our results showing significant improvements in quality across all metrics compared to existing methods.
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