MEDPNet: Achieving High-Precision Adaptive Registration for Complex Die Castings

arXiv:2403.09996v1 Announce Type: new
Abstract: Due to their complex spatial structure and diverse geometric features, achieving high-precision and robust point cloud registration for complex Die Castings has been a significant challenge in the die-casting industry. Existing point cloud registration methods primarily optimize network models using well-established high-quality datasets, often neglecting practical application in real scenarios. To address this gap, this paper proposes a high-precision adaptive registration method called Multiscale Efficient Deep Closest Point (MEDPNet) and introduces a die-casting point cloud …

abstract arxiv challenge cloud cs.cv datasets die diverse features industry network practical precision quality registration robust spatial type