Spectrum Random Masking for Generalization in Image-based Reinforcement Learning Y angru Huang

To handle this problem, a natural approach is to increase the data diversity by image based augmentations. However, different with most vision tasks such as classification and detection, RL tasks are not always invariant to spatial based augmentations due to the entanglement of environment dynamics and visual appearance.