The field of 3D Gaussian Splatting (3DGS) is rapidly advancing with a focus on improving rendering quality, efficiency, and scalability. Recent developments have led to the creation of innovative methods for accelerating 3DGS, such as enhancing GPU triangle rasterizers and proposing optimized minimal Gaussian representations. These advancements have resulted in significant reductions in computation time and improvements in rendering quality, making 3DGS a more viable option for real-time applications. Furthermore, researchers have explored the use of 3DGS in novel view synthesis, global illumination, and watermarking, demonstrating its potential in various areas of computer graphics and vision. Notable papers in this area include GauRast, which proposes an acceleration strategy for 3DGS by leveraging the similarities between the 3DGS pipeline and the conventional graphics pipeline in modern GPUs. Optimized Minimal 3D Gaussian Splatting is another noteworthy paper that significantly reduces storage requirements while maintaining high rendering quality. ProtoGS, GaussianFocus, and StableGS also present innovative approaches to improving 3DGS, such as learning Gaussian prototypes, incorporating patch attention algorithms, and eliminating floater artifacts.