Building information modelling (BIM) is evolving significantly in the architecture, engineering
and construction industries. BIM involves various remote-sensing tools, procedures and …

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 …

As a fundamental problem in computer vision, 3D point cloud registration (PCR) aims to
seek the optimal pose to align a point cloud pair. In this paper, we present a 3D registration …

Abstract Domain Adaptive Object Detection (DAOD) leverages a labeled domain to learn an
object detector generalizing to a novel domain free of annotations. Recent advances align …

Autonomous driving perception has made significant strides in recent years, but accurately
sensing the environment using a single sensor remains a daunting task. This review offers a …

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 …

An ideal point cloud registration framework should have superior accuracy, acceptable
efficiency, and strong generalizability. However, this is highly challenging since existing …

We explore the effect of geometric structure descriptors on extracting reliable
correspondences and obtaining accurate registration for point cloud registration. The point …

Deep point cloud registration methods face challenges to partial overlaps and rely on
labeled data. To address these issues, we propose UDPReg, an unsupervised deep …

We present RoReg, a novel point cloud registration framework that fully exploits oriented
descriptors and estimated local rotations in the whole registration pipeline. Previous …