Shape Assembly

Shape assembly focuses on computationally reconstructing a complete object from its constituent parts, addressing challenges in both geometric and semantic understanding. Current research emphasizes learning-based approaches, employing techniques like point cloud matching, SE(3) equivariant representations, and hierarchical graph learning to efficiently determine part poses and optimize for both structural accuracy and joint alignment. This field is crucial for advancements in robotics, CAD modeling, and medical imaging, enabling applications such as automated assembly, fracture reconstruction, and the generation of realistic anatomical models for simulations.