203 citations · 353 across the 13 of their papers we have counts for
3 papers · 1 filter
SpawnNet: Learning Generalizable Visuomotor Skills from Pre-trained Networks
Xingyu Lin, John So, Sashwat Mahalingam +2
The existing internet-scale image and video datasets cover a wide range of everyday objects and tasks, bringing the potential of learning policies that generalize in diverse scenar…
Masked World Models for Visual Control
Younggyo Seo, Danijar Hafner, Hao Liu +4
Visual model-based reinforcement learning (RL) has the potential to enable sample-efficient robot learning from visual observations. Yet the current approaches typically train a si…
Towards More Generalizable One-shot Visual Imitation Learning
Zhao Mandi, Fangchen Liu, Kimin Lee +1
A general-purpose robot should be able to master a wide range of tasks and quickly learn a novel one by leveraging past experiences. One-shot imitation learning (OSIL) approaches t…