Shape Deformation

Shape deformation research focuses on accurately modeling and manipulating the changes in an object's form, crucial for robotics, computer graphics, and other fields. Current efforts concentrate on developing robust and efficient methods for representing and predicting deformations, employing techniques like neural signed distance fields (NSDFs), generalized cylinders, and transformer-based networks, often incorporating spectral and spatial information for improved accuracy and generalization. These advancements are improving the ability to reconstruct and control shape changes in real-time, with applications ranging from robotic manipulation of deformable objects to accurate 3D shape modeling and interpolation. The ultimate goal is to create more versatile and adaptable systems capable of handling complex, non-rigid deformations in various contexts.