Registration is a transformation estimation problem between two point clouds, which has a
unique and critical role in numerous computer vision applications. The developments of …

This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …

We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult …

Despite recent success in incorporating learning into point cloud registration, many works
focus on learning feature descriptors and continue to rely on nearest-neighbor feature …

We introduce PREDATOR, a model for pairwise pointcloud registration with deep attention
to the overlap region. Different from previous work, our model is specifically designed to …

We study the problem of extracting correspondences between a pair of point clouds for
registration. For correspondence retrieval, existing works benefit from matching sparse …

Abstract We present Deep Global Registration, a differentiable framework for pairwise
registration of real-world 3D scans. Deep global registration is based on three modules: a 6 …

Removing outlier correspondences is one of the critical steps for successful feature-based
point cloud registration. Despite the increasing popularity of introducing deep learning …

Abstract Iterative Closest Point (ICP) solves the rigid point cloud registration problem
iteratively in two steps:(1) make hard assignments of spatially closest point …

We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …