The field of 3D reconstruction and rendering is witnessing significant advancements with the development of 3D Gaussian Splatting (3DGS) techniques. Researchers are focusing on improving the efficiency, quality, and scalability of 3DGS methods, enabling real-time rendering and high-quality novel view synthesis. Notably, innovations in compression, calibration, and optimization are driving the field forward. These advancements have the potential to revolutionize various applications, including robotics, autonomous driving, and virtual reality. Noteworthy papers include: Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization, which achieves a 45x reduction in memory consumption while maintaining competitive reconstruction quality. Micro-splatting: Maximizing Isotropic Constraints for Refined Optimization in 3D Gaussian Splatting, which introduces a novel framework for refined optimization, resulting in denser and more detailed 3D reconstructions.