Three-dimensional point cloud registration is an important field in computer vision. Recently,
due to the increasingly complex scenes and incomplete observations, many partial-overlap …

Point cloud registration is a key problem in the application of computer vision to robotics,
autopilot and other fields. However, because the object is partially covered up or the …

Point cloud registration is a critical task in many 3-D computer vision studies, aiming to find a
rigid transformation that aligns one point cloud with another. In this article, we propose a …

Point cloud registration is the process of aligning point clouds collected at different locations
of the same scene, which transforms the data into a common coordinate system and forms …

Unsupervised point cloud registration algorithm usually suffers from the unsatisfied
registration precision in the partially overlapping problem due to the lack of effective inlier …

Partial point cloud registration aims to transform partial scans into a common coordinate
system. It is an important preprocessing step to generate complete 3D shapes. Although …

The registration of point clouds is a key ingredient of LiDAR-based SLAM systems and
mapping approaches. A challenging task in this context is finding the right data association …

The research groups in computer vision, graphics, and machine learning have dedicated a
substantial amount of attention to the areas of 3D object reconstruction, augmentation, and …

The use of Transformer-based networks has been proposed for the processing of general
point clouds. However, there has been little research related to multispectral LiDAR point …

Artificial Intelligence-based systems are required to interact with dynamic environments to
continuously learn, retain and effectively utilize knowledge. Present AI-based systems …