Gaussian Map

Gaussian maps represent 3D scenes using collections of 3D Gaussian distributions, offering a flexible and efficient alternative to traditional volumetric methods. Current research focuses on improving the accuracy, speed, and robustness of Gaussian map construction and utilization, particularly within simultaneous localization and mapping (SLAM) systems and novel view synthesis, often incorporating techniques like Gaussian splatting and iterative closest point (ICP) algorithms. These advancements are driving improvements in robotics, augmented/virtual reality, and applications requiring high-fidelity 3D scene reconstruction and manipulation, such as digital human generation and agricultural phenotyping. The ability to generate high-quality, real-time 3D representations from various data sources is a key driver of this research.