3D Hand Object Contact

3D hand-object contact modeling aims to accurately represent the interaction between a hand and the objects it manipulates, crucial for tasks like grasp planning and object reconstruction from images. Recent research focuses on incorporating natural language descriptions to guide contact modeling, using diffusion models and variational autoencoders to generate realistic contact maps from various input modalities (e.g., point clouds, images). These advancements improve the accuracy and realism of 3D hand-object interactions, impacting robotics (e.g., improving grasping in cluttered environments) and computer vision (e.g., enhancing 3D object reconstruction from single images). The development of new datasets with detailed contact annotations is also a key area of progress.