Shape Matching

Shape matching aims to establish correspondences between points on two or more shapes, even when they are deformed or partially observed. Current research emphasizes robust methods for non-rigid 3D shape matching, often employing deep learning architectures like functional maps and transformers, as well as combinatorial optimization techniques to ensure geometric consistency. These advancements are crucial for applications ranging from medical image analysis (e.g., precise vertebrae segmentation) to robotics (e.g., object assembly) and computer graphics (e.g., shape interpolation and animation), improving accuracy and efficiency in various fields.