Point Based Network

Point-based networks process data as individual points, offering advantages in efficiency and scalability compared to voxel-based methods, particularly for sparse data like LiDAR and event camera streams. Current research focuses on improving the efficiency and accuracy of these networks through architectural innovations such as hierarchical structures, optimized feature extraction (e.g., using graph convolutional networks and attention mechanisms), and techniques to enhance point cloud density and quality. These advancements are driving improvements in applications ranging from 3D object detection in autonomous driving to data extraction from scientific charts and efficient 3D semantic segmentation, demonstrating the growing importance of point-based approaches in various fields.