Large Scale Point Cloud

Large-scale point cloud processing focuses on efficiently managing and analyzing massive 3D datasets, addressing challenges in storage, rendering, and analysis. Current research emphasizes developing novel algorithms and architectures, such as graph neural networks and deep learning-based compression techniques, to improve speed and accuracy in tasks like semantic segmentation, object detection, and surface reconstruction. These advancements are crucial for applications in autonomous driving, robotics, and scientific visualization, enabling real-time processing of increasingly complex 3D environments and datasets.