3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance Fields (NeRF). This technique has found diverse applications in areas such as robotics, urban mapping, autonomous navigation, and virtual reality/augmented reality, just name a few. Given the growing popularity and expanding research in 3D Gaussian Splatting, this paper presents a comprehensive survey of relevant papers from the past year. We organize the survey into taxonomies based on characteristics and applications, providing an introduction to the theoretical underpinnings of 3D Gaussian Splatting. Our goal through this survey is to acquaint new researchers with 3D Gaussian Splatting, serve as a valuable reference for seminal works in the field, and inspire future research directions, as discussed in our concluding section.

翻译：三维高斯泼溅（3D-GS）已成为计算机图形学领域的一项重要进展，它提供了一种显式的场景表示方法，并能够在不依赖神经网络（如神经辐射场NeRF）的情况下实现新颖视角合成。该技术已在机器人学、城市测绘、自主导航以及虚拟现实/增强现实等多个领域得到广泛应用。鉴于三维高斯泼溅日益增长的热度与不断扩展的研究，本文对过去一年中的相关论文进行了全面综述。我们依据技术特点与应用领域构建了分类体系，并介绍了三维高斯泼溅的理论基础。通过本综述，我们旨在帮助新研究者熟悉三维高斯泼溅技术，为该领域的开创性工作提供有价值的参考，并如结论部分所讨论的，启发未来的研究方向。