三维高斯拼接技术的最新进展

IF 17.3 3区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING Computational Visual Media Pub Date : 2024-07-08 DOI:10.1007/s41095-024-0436-y
Tong Wu, Yu-Jie Yuan, Ling-Xiao Zhang, Jie Yang, Yan-Pei Cao, Ling-Qi Yan, Lin Gao
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引用次数: 0

摘要

三维高斯拼接(3DGS)的出现大大加快了新型视图合成的渲染速度。神经辐射场(NeRFs)等神经隐式表示法通过位置和视点条件神经网络来表示三维场景,而三维高斯拼接法则不同,它利用一组高斯椭球来模拟场景,这样就可以通过将高斯椭球光栅化到图像中来实现高效渲染。除了快速渲染外,三维高斯拼接的显式表示法还有助于完成动态重建、几何编辑和物理模拟等下游任务。考虑到这一领域日新月异的变化和日益增多的作品,我们对最近的三维高斯拼接方法进行了文献综述,这些方法按功能可大致分为三维重建、三维编辑和其他下游应用。此外,我们还介绍了传统的基于点的渲染方法和三维高斯拼接的渲染公式,以帮助读者理解这项技术。本研究旨在帮助初学者快速入门这一领域,并为有经验的研究人员提供全面的概述,从而促进三维高斯拼接表示法的未来发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Recent advances in 3D Gaussian splatting

The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) that represent a 3D scene with position and viewpoint-conditioned neural networks, 3D Gaussian splatting utilizes a set of Gaussian ellipsoids to model the scene so that efficient rendering can be accomplished by rasterizing Gaussian ellipsoids into images. Apart from fast rendering, the explicit representation of 3D Gaussian splatting also facilitates downstream tasks like dynamic reconstruction, geometry editing, and physical simulation. Considering the rapid changes and growing number of works in this field, we present a literature review of recent 3D Gaussian splatting methods, which can be roughly classified by functionality into 3D reconstruction, 3D editing, and other downstream applications. Traditional point-based rendering methods and the rendering formulation of 3D Gaussian splatting are also covered to aid understanding of this technique. This survey aims to help beginners to quickly get started in this field and to provide experienced researchers with a comprehensive overview, aiming to stimulate future development of the 3D Gaussian splatting representation.

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来源期刊
Computational Visual Media
Computational Visual Media Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
16.90
自引率
5.80%
发文量
243
审稿时长
6 weeks
期刊介绍: Computational Visual Media is a peer-reviewed open access journal. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media. Computational Visual Media publishes articles that focus on, but are not limited to, the following areas: • Editing and composition of visual media • Geometric computing for images and video • Geometry modeling and processing • Machine learning for visual media • Physically based animation • Realistic rendering • Recognition and understanding of visual media • Visual computing for robotics • Visualization and visual analytics Other interdisciplinary research into visual media that combines aspects of computer graphics, computer vision, image and video processing, geometric computing, and machine learning is also within the journal''s scope. This is an open access journal, published quarterly by Tsinghua University Press and Springer. The open access fees (article-processing charges) are fully sponsored by Tsinghua University, China. Authors can publish in the journal without any additional charges.
期刊最新文献
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