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cs.LG2024
DIDA: Denoised Imitation Learning based on Domain Adaptation
Kaichen Huang, Hai-Hang Sun, Shenghua Wan +4
Imitating skills from low-quality datasets, such as sub-optimal demonstrations and observations with distractors, is common in real-world applications. In this work, we focus on th…
cs.LG2024
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
Yucen Wang, Shenghua Wan, Le Gan +2
Model-based methods have significantly contributed to distinguishing task-irrelevant distractors for visual control. However, prior research has primarily focused on heterogeneous…