Lorand Cheng

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos

Action-labeled data for robotics is scarce and expensive, limiting the generalization of learned policies. In contrast, vast amounts of action-free video data are readily available, but translating these observations into effective policies remains a challenge. We introduce AMPLIFY, a framework that…