Complex Object Shape

Understanding and manipulating complex object shapes is a crucial challenge across diverse fields, driving research into efficient representation, abstraction, and interaction methods. Current efforts focus on developing novel algorithms and model architectures, including diffusion models for grasp generation, deformable models integrated with transformers for 3D shape reconstruction from images, and physics-informed neural networks for fluid dynamics simulation around complex geometries. These advancements are improving robotic manipulation, computer vision, and computational fluid dynamics, enabling more accurate and efficient solutions for tasks ranging from object reorientation to industrial process optimization.