LiDAR Depth

LiDAR depth research focuses on generating accurate and dense depth maps from sparse LiDAR point clouds, often integrating data from other sensors like cameras and IMUs for improved accuracy and robustness. Current efforts concentrate on developing sophisticated algorithms, including neural networks like PENet and DenseDepth, to achieve depth completion, handle noise and outliers, and improve depth estimation in challenging scenarios like long distances or occlusions. These advancements are crucial for applications such as autonomous driving and robotics, enabling more reliable 3D scene understanding and improved navigation capabilities.