Point Cloud Completion

Point Cloud Completion refers to the process in computer vision where algorithms are used to supplement and repair incomplete or sparse point cloud data to generate a complete and dense 3D model. The goal is to improve the quality and usability of point cloud data, ensuring the accuracy of 3D reconstruction. This technology has significant application value in areas such as autonomous driving, robot navigation, and virtual reality, effectively enhancing the system's perception capabilities and interaction experience.