Cloth Simulation

Cloth simulation aims to realistically model the behavior of cloth under various conditions, primarily for applications in computer graphics and robotics. Current research focuses on improving the accuracy and efficiency of simulations, particularly addressing self-collisions and generalizing to unseen garment types and body shapes, often employing neural networks (e.g., graph neural networks, transformers) and physics-based models integrated with deep learning frameworks. These advancements are crucial for creating realistic virtual avatars, improving virtual try-on experiences, and enabling more sophisticated robotic manipulation of cloth.