EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets 事件

EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets arXiv:2606.08057v1 Announce Type: cross Abstract: Egocentric RGB-D videos offer a natural source of human dexterous manipulation demonstrations, but existing data is difficult to use for robot learning because object pose, geometry, and contact information are often missing or require pre-scanned object assets. We present EgoAERO, the first framework that learns dexterous manipulation from a single ego