3D Gaussian splatting technologies and extensions: A review

In recent years, 3D Gaussian Splatting (3DGS) has achieved remarkable progress in the field of novel view synthesis. Unlike implicit neural radiance field (NeRF) methods that primarily focus on positional and viewpoint transformations, 3DGS leverages millions of Gaussian ellipsoids for scene reconstruction and employs parallel differentiable rasterization to substantially improve rendering efficiency. Given the rapid advancement and promising prospects of this technique, this survey presents a systematic overview of recent developments in 3DGS. We provide a detailed exposition of the fundamental theory underlying 3DGS, along with relevant benchmark datasets. Uniquely, this work organizes existing optimization strategies according to the stages of the Gaussian splatting pipeline. In addition, we review various downstream applications based on 3DGS and discuss prospective research directions. This survey aims to serve as a valuable reference for researchers across all stages of engagement and to foster further advancements in 3DGS.