Yingqian Huang

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Affordance Correspondence

Despite the recent success of modern imitation learning methods in robot manipulation, their performance is often constrained by geometric variations due to limited data diversity. Leveraging powerful 3D generative models and vision foundation models (VFMs), the proposed AffordGen framework overcome