Complex Deformation

Complex deformation modeling focuses on accurately representing and predicting the changes in shape and form of objects, particularly those undergoing significant non-rigid transformations. Current research emphasizes developing robust and efficient methods, employing techniques like neural networks (including convolutional and transformer architectures), mesh-based approaches, and physics-informed models to handle diverse deformation types and improve generalization across different objects and forces. These advancements have significant implications for various fields, including robotics (manipulation of deformable objects), medical imaging (accurate 3D reconstruction of organs), and computer graphics (realistic simulation of clothing and other materials).