AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence 事件

AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence arXiv:2604.10579v2 Announce Type: replace-cross Abstract: 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 overcomes this limitation by utilizing