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20162022
most citedSocratic Models: Composing Zero-Shot Multimodal Reasoning with Language

173 citations · 234 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.RO20212 cited

Self-Supervised Disentangled Representation Learning for Third-Person Imitation Learning

Jinghuan Shang, Michael S. Ryoo

Humans learn to imitate by observing others. However, robot imitation learning generally requires expert demonstrations in the first-person view (FPV). Collecting such FPV videos f…

cs.RO2021

Visionary: Vision architecture discovery for robot learning

Iretiayo Akinola, Anelia Angelova, Yao Lu +5

We propose a vision-based architecture search algorithm for robot manipulation learning, which discovers interactions between low dimension action inputs and high dimensional visua…

cs.RO20196 cited

Model-based Behavioral Cloning with Future Image Similarity Learning

Alan Wu, AJ Piergiovanni, Michael S. Ryoo

We present a visual imitation learning framework that enables learning of robot action policies solely based on expert samples without any robot trials. Robot exploration and on-po…

cs.RO2018

Learning Real-World Robot Policies by Dreaming

AJ Piergiovanni, Alan Wu, Michael S. Ryoo

Learning to control robots directly based on images is a primary challenge in robotics. However, many existing reinforcement learning approaches require iteratively obtaining milli…

cs.RO20176 cited

Learning Social Affordance Grammar from Videos: Transferring Human Interactions to Human-Robot Interactions

Tianmin Shu, Xiaofeng Gao, Michael S. Ryoo +1

In this paper, we present a general framework for learning social affordance grammar as a spatiotemporal AND-OR graph (ST-AOG) from RGB-D videos of human interactions, and transfer…

cs.RO2016

Learning Social Affordance for Human-Robot Interaction

Tianmin Shu, M. S. Ryoo, Song-Chun Zhu

In this paper, we present an approach for robot learning of social affordance from human activity videos. We consider the problem in the context of human-robot interaction: Our app…