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.
3D高斯喷溅（3D-GS）已成为计算机图形学领域的一个重要进步，提供了明确的场景表示和新视角合成，而不依赖于神经网络，如神经辐射场（NeRF）。这项技术在机器人学、城市绘图、自主导航、虚拟现实/增强现实等多个领域找到了广泛应用。鉴于3D高斯喷溅的日益流行和研究的不断扩展，本文提出了对过去一年相关论文的全面调查。我们根据特征和应用组织了调查分类，为3D高斯喷溅的理论基础提供了介绍。通过这项调查，我们的目标是让新研究人员熟悉3D高斯喷溅，为该领域的重要工作提供宝贵的参考，并启发未来的研究方向，如我们在结论部分所讨论的。