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一项基于3D高斯喷涂的表面重建调查
Zheng Xu1, Gang Chen1, Feng Li1
1Institute of Geographical Spatial Information, Information Engineering University, Zhengzhou, China.
PeerJ. Computer science
|September 24, 2025
概括
本次调查探讨了3D表面重建方法,重点关注3D高斯喷射 (3D GS) 和神经辐射场 (NeRFs). 它为理解3D表示,重建技术和未来研究方向提供了路线图.
科学领域:
- 计算机图形 计算机图形
- 3D视觉视觉 3D视觉视觉是什么?
- 几何建模 几何建模
背景情况:
- 表面重建在计算机图形学中至关重要.
- 最近的进展包括神经辐射场 (NeRFs) 和3D高斯喷射 (3D GS).
- 快速增长需要对当前的方法进行结构化的概述.
研究的目的:
- 介绍3D模型表面重建的核心方法.
- 建立一个结构化的路线图,涵盖3D表示,重建方法,数据集和应用.
- 为该领域的研究人员提供宝贵的资源.
主要方法:
- 专注于使用3D高斯数作为中心框架的3D表示.
- 提供了基于3D高斯喷涂的表面重建方法的全面概述.
- 将算法分类为场景表示,高斯优化和表面结构提取.
主要成果:
- 介绍了3D高斯函数作为表面重建的关键表示.
- 细节演变的重建方法利用3D高斯斯裂纹.
- 审查可用的数据集,应用程序,并确定当前的挑战.
结论:
- 该调查为3D表面重建研究提供了一个结构化的路线图.
- 它突出了3D高斯斯喷在最近的进步中的重要性.
- 它建议未来的研究方向,以促进3D重建技术的进步.
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