Over recent decades, 3D point clouds have been a popular data source applied in automatic
change detection in a wide variety of applications. Compared with 2D images, using 3D …

Deep learning (DL) on point clouds holds significant potential in the construction industry,
yet no comprehensive review has thoroughly summarized its applications and shortcomings …

Point cloud segmentation is essential for studying the 3D spatial characteristics of plants.
Notably, the segmentation accuracy greatly impacts subsequent 3D plant phenotypes …

High-precision localization in an unknown environment is the fundamental requirement of
autonomous vehicle for safe advanced driving. Cooperative localization has obvious …

Point cloud registration, which effectively coincides the source and target point clouds, is
generally implemented by geometric metrics or feature metrics. In terms of resistance to …

Three-dimensional reconstruction technology has demonstrated broad application potential
in the industrial, construction, medical, forestry, agricultural, and pastural sectors in the last …

Simultaneously localization and mapping (SLAM) has been widely used in autonomous
mobile systems to fulfill autonomous navigation. Relocalization plays an important role in …

Feature extraction is a key step for deep-learning-based point cloud registration. In the
correspondence-free point cloud registration task, the previous work commonly aggregates …

For point cloud registration (PCR), a matching matrix is critical. Unfortunately, the existing
approaches do not explicitly devise schemes to refine the matching matrix. Furthermore …

Point cloud registration plays an essential role in many areas, such as computer vision and
robotics. However, traditional feature-based registration requires handcrafted descriptors for …