3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view images into explicit 3D Gaussian representations through efficient training, and achieve real-time rendering of novel views. This survey aims to analyze existing 3DGS-related works from multiple intersecting perspectives, including related tasks, technologies, challenges, and opportunities. The primary objective is to provide newcomers with a rapid understanding of the field and to assist researchers in methodically organizing existing technologies and challenges. Specifically, we delve into the optimization, application, and extension of 3DGS, categorizing them based on their focuses or motivations. Additionally, we summarize and classify nine types of technical modules and corresponding improvements identified in existing works. Based on these analyses, we further examine the common challenges and technologies across various tasks, proposing potential research opportunities.
3D 高斯溅射(3DGS)已经成为一种突出的技术，有潜力成为 3D 表示的主流方法。它可以通过高效的训练将多视角图像有效地转换为显式的 3D 高斯表示，并实现新视角的实时渲染。本综述旨在从多个交叉的角度分析现有的 3DGS 相关工作，包括相关任务、技术、挑战和机遇。主要目标是帮助新人快速了解该领域，并协助研究人员系统地组织现有技术和挑战。 具体而言，我们深入研究了 3DGS 的优化、应用和扩展，并根据它们的关注点或动机进行分类。此外，我们总结和分类了在现有工作中发现的九种技术模块和相应的改进。基于这些分析，我们进一步研究了各种任务中的共同挑战和技术，提出了潜在的研究机会。