MoReg: Minimal-Overlap 3D Point Cloud Registration via Visibility-Aware Matching

3D point cloud registration is widely used in ap-plications such as autonomous navigation, 3D re-construction, mapping, and scene understanding ,where partially overlapping observations must be aligned. Registration under minimal over-lap (10–30%) remains challenging, as limited shared regions often lead to unreliable correspondences. Most existing methods rely on sufficient overlap, which affects performance in such set-tings. We introduce MOREG, a framework for minimal-overlap registration that uses visibility-aware matching and overlap-guided feature inter-action to focus matching on shared regions. We evaluate MOREG on ModelNet40 under varying overlap conditions and validate it on a real-world dataset collected using a UR7e robot across different overlap pairs. Our method consistently im-proves performance over PREDATOR in minimal-overlap settings