PRoGS: Progressive Rendering of Gaussian Splats

Brent Zoomers, Maarten Wijnants, Ivan Molenaers, Joni Vanherck, Jeroen Put, Lode Jorissen, Nick Michiels
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Abstract

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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PRoGS:高斯花斑渐进渲染
在过去的一年里,三维高斯拼接技术(3DGS)因其能够以感知准确的方式表现三维场景而备受关注。然而,由于必须存储每个拼接的单独数据,因此需要大量存储空间。虽然压缩技术通过减少内存占用提供了一种潜在的解决方案,但它们仍然需要在渲染场景的任何部分之前检索整个场景。在本作品中,我们介绍了一种逐步渲染此类场景的新方法,目的是在不将整个场景载入内存的情况下,尽可能早地显示与最终场景接近的可见内容。这种方法既有利于受内存限制的设备上渲染应用,也有利于希望尽量减少带宽使用的流媒体应用。为了实现这一目标,我们近似计算了每个高斯对最终场景的贡献,并构建了将它们纳入渲染过程的优先顺序。此外,我们还证明了我们的方法可以与现有的压缩方法相结合,逐步渲染(和流式传输)3DGS 场景,通过集中处理场景中最重要的部分来优化带宽使用。总之,我们的工作为使远程托管的 3DGS 内容更快地供终端用户在over-the-top 消费场景中访问奠定了基础,我们的结果表明,与现有方法相比,所有指标的质量都有显著提高。
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