Outlier removal is a critical part of feature-based point cloud registration. In this article, we
revisit the model generation and selection of the classic RANSAC approach for fast and …

Point cloud registration is a task to estimate the rigid transformation between two unaligned
scans, which plays an important role in many computer vision applications. Previous …

Point cloud registration is a crucial task in computer vision and 3D reconstruction, aiming to
align multiple point clouds to achieve globally consistent geometric structures. However …

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 …

The presence of partial or low overlaps in real point cloud pairs poses significant challenges
to obtain robust registration. There is an absence of a unified framework that localizes …

Efficiently finding optimal correspondences between point clouds is crucial for solving both
rigid and non-rigid point cloud registration problems. Existing methods often rely on …

Point cloud registration is a fundamental task in computer vision. Recent Transformer based
methods for point cloud registration take advantage of the interaction modeling ability of the …

Point cloud registration plays a crucial role in various fields, including robotics, computer
graphics, and medical imaging. This process involves determining spatial relationships …

Point Cloud Registration is a fundamental and challenging problem in 3D computer vision.
Recent works often utilize geometric structure features in downsampled points (patches) to …

Establishing reliable correspondences is essential for registration tasks such as 3D and
2D3D registration. Existing methods commonly leverage geometric or semantic point …