GES：通用指數塗抹技術用於高效輻射場渲染

摘要

在3D高斯飛濺技術的進展顯著加快了3D重建和生成的速度。然而，這可能需要大量的高斯分布，這會造成相當大的記憶體占用。本文介紹了GES（廣義指數飛濺），這是一種新穎的表示法，採用廣義指數函數（GEF）來建模3D場景，需要更少的粒子來表示場景，因此在效率上顯著優於高斯飛濺方法，並具有可插拔替換高斯工具的能力。GES在理論和實證上在有原則的1D設置和現實的3D場景中得到驗證。顯示它能更準確地表示具有銳利邊緣的信號，這對於高斯分布來說通常是具有困難的，因為它們具有固有的低通特性。我們的實證分析表明，GEF在擬合自然發生的信號（例如方形、三角形和抛物線信號）方面優於高斯分布，從而減少了高斯飛濺的記憶體占用量增加的需求。通過頻率調製損失的幫助，GES在新視角合成基準測試中實現了競爭性的性能，同時只需要不到高斯飛濺的一半記憶體存儲空間，並將渲染速度提高了多達39%。代碼可在項目網站https://abdullahamdi.com/ges 上獲得。

English

Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However, it may require a large number of Gaussians, which creates a substantial memory footprint. This paper introduces GES (Generalized Exponential Splatting), a novel representation that employs Generalized Exponential Function (GEF) to model 3D scenes, requiring far fewer particles to represent a scene and thus significantly outperforming Gaussian Splatting methods in efficiency with a plug-and-play replacement ability for Gaussian-based utilities. GES is validated theoretically and empirically in both principled 1D setup and realistic 3D scenes. It is shown to represent signals with sharp edges more accurately, which are typically challenging for Gaussians due to their inherent low-pass characteristics. Our empirical analysis demonstrates that GEF outperforms Gaussians in fitting natural-occurring signals (e.g. squares, triangles, and parabolic signals), thereby reducing the need for extensive splitting operations that increase the memory footprint of Gaussian Splatting. With the aid of a frequency-modulated loss, GES achieves competitive performance in novel-view synthesis benchmarks while requiring less than half the memory storage of Gaussian Splatting and increasing the rendering speed by up to 39%. The code is available on the project website https://abdullahamdi.com/ges .

GES：通用指數塗抹技術用於高效輻射場渲染

GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering

摘要

Summary

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