TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance

Yuyang Liu, Chuan Wen, Yihang Hu +2

Designing dense rewards is crucial for reinforcement learning (RL), yet in robotics it often demands extensive manual effort and lacks scalability. One promising solution is to vie…