We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods have shown great potential through bypassing the detection …

3D point cloud registration is fragile to outliers, which are labeled as the points without
corresponding points. To handle this problem, a widely adopted strategy is to estimate the …

Transformation equivariance has been widely investigated in 3D point cloud representation
learning for more informative descriptors, which formulates the change of the representation …

High‐confidence overlap prediction and accurate correspondences are critical for cutting‐
edge models to align paired point clouds in a partial‐to‐partial manner. However, there …

Computational intelligence (CI) uses applied computational methods for problem-solving
inspired by the behavior of humans and animals. Biological systems are used to construct …

Many point cloud registration methods rely on establishing correspondence pairs in order to
solve the registration problem. However, their performance significantly deteriorates when …

Point cloud registration technology, by precisely aligning repair components with the original
artifacts, can accurately record the geometric shape of cultural heritage objects and …

Point cloud registration is a fundamental task in the 3D vision field. Many previous works
adopt the regression model to estimate the transformation parameters. However, these …

Most studies on point cloud registration have established the problem in the case of ideal
point cloud data. Although the state-of-the-art approaches have achieved amazing results …

Point cloud registration is not only a key step in constructing high-precision 3-D maps, but is
also of great significance in fields such as autonomous navigation, environmental …