LiDAR Data Augmentation

LiDAR data augmentation aims to improve the performance of 3D perception systems by artificially expanding limited LiDAR datasets. Current research focuses on generating realistic synthetic data, often integrating information from other sensors like cameras to enhance point cloud density and detail, or employing physics-based simulations to model challenging weather conditions. These techniques, implemented through various algorithms including neural networks and geometric transformations, are crucial for advancing autonomous driving, robotics, and 3D modeling applications by mitigating data scarcity and improving the robustness of LiDAR-based systems.