26 citations · 53 across the 4 of their papers we have counts for
6 papers
Discovering Objects that Can Move
Zhipeng Bao, Pavel Tokmakov, Allan Jabri +3
This paper studies the problem of object discovery -- separating objects from the background without manual labels. Existing approaches utilize appearance cues, such as color, text…
Space-Time Correspondence as a Contrastive Random Walk
Allan Jabri, Andrew Owens, Alexei A. Efros
This paper proposes a simple self-supervised approach for learning a representation for visual correspondence from raw video. We cast correspondence as prediction of links in a spa…
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
Richard Li, Allan Jabri, Trevor Darrell +1
Learning robotic manipulation tasks using reinforcement learning with sparse rewards is currently impractical due to the outrageous data requirements. Many practical tasks require…
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri, Kyle Hsu, Ben Eysenbach +3
In principle, meta-reinforcement learning algorithms leverage experience across many tasks to learn fast reinforcement learning (RL) strategies that transfer to similar tasks. Howe…
Learning Correspondence from the Cycle-Consistency of Time
Xiaolong Wang, Allan Jabri, Alexei A. Efros
We introduce a self-supervised method for learning visual correspondence from unlabeled video. The main idea is to use cycle-consistency in time as free supervisory signal for lear…
Universal Planning Networks
Aravind Srinivas, Allan Jabri, Pieter Abbeel +2
A key challenge in complex visuomotor control is learning abstract representations that are effective for specifying goals, planning, and generalization. To this end, we introduce…