Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

no code implementations • 3 Feb 2024 • Haoran Li, ZiCheng Zhang, Wang Luo, Congying Han, Yudong Hu, Tiande Guo, Shichen Liao

Establishing robust policies is essential to counter attacks or disturbances affecting deep reinforcement learning (DRL) agents.

Adversarial Robustness Q-Learning

Action Unit Memory Network for Weakly Supervised Temporal Action Localization

no code implementations • CVPR 2021 • Wang Luo, Tianzhu Zhang, Wenfei Yang, Jingen Liu, Tao Mei, Feng Wu, Yongdong Zhang

In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.

Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1