3D Gaussian Splatting Rasterization: A Survey

3D scene reconstruction and novel view synthesis have undergone a paradigm shift with the advent of 3D Gaussian Splatting (3DGS). Unlike computationally intensive volumetric rendering, 3DGS leverages a point-based representation with a differentiable tile-based rasterizer. This elegant synthesis achieves state-of-the-art visual fidelity at real-time rendering frame rates. As the 3DGS literature grows rapidly, existing surveys have primarily organized the field around downstream applications. In contrast, this survey provides a rasterization-centric analysis, treating the differentiable rasterization pipeline as the core computational engine of 3DGS. We begin by delineating the mathematical foundations of Gaussian splatting and tracing its lineage from classical volume rendering. Subsequently, we propose a fine-grained taxonomy that categorizes the literature across three hierarchical dimensions: (1) representation and optimization, (2) rasterization pipeline innovations, and (3) scenario-driven rasterization extensions. By deconstructing these algorithmic advances in rasterization, we offer quantitative insights into hardware-algorithm co-design and outline critical trajectories for future research. To support the community, we maintain a continually updated repository of relevant literature and open-source implementations at https://github.com/3DAgentWorld/Advanced3DGS.