b'Deepak Pathak'

RMA: Rapid Motor Adaptation for Legged Robots

Successful real-world deployment of legged robots would require them to ...
07/08/2021 ∙ by Ashish Kumar, et al. ∙ 11 ∙ share

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Auto-Tuned Sim-to-Real Transfer

Policies trained in simulation often fail when transferred to the real w...
04/15/2021 ∙ by Yuqing Du, et al. ∙ 0 ∙ share

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Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image

We present Worldsheet, a method for novel view synthesis using just a si...
12/17/2020 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation

A majority of approaches solve the problem of video frame interpolation ...
12/15/2020 ∙ by Tarun Kalluri, et al. ∙ 7 ∙ share

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Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion

Hierarchical learning has been successful at learning generalizable loco...
08/27/2020 ∙ by Tianyu Li, et al. ∙ 0 ∙ share

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Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

Learning long-term dynamics models is the key to understanding physical ...
08/05/2020 ∙ by Haozhi Qi, et al. ∙ 2 ∙ share

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One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control

Reinforcement learning is typically concerned with learning control poli...
07/09/2020 ∙ by Wenlong Huang, et al. ∙ 9 ∙ share

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Locally Masked Convolution for Autoregressive Models

High-dimensional generative models have many applications including imag...
06/22/2020 ∙ by Ajay Jain, et al. ∙ 61 ∙ share

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Planning to Explore via Self-Supervised World Models

Reinforcement learning allows solving complex tasks, however, the learni...
05/12/2020 ∙ by Ramanan Sekar, et al. ∙ 2 ∙ share

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Sparse Graphical Memory for Robust Planning

To operate effectively in the real world, artificial agents must act fro...
03/13/2020 ∙ by Michael (Misha) Laskin, et al. ∙ 17 ∙ share

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Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller

We study a generalized setup for learning from demonstration to build an...
11/21/2019 ∙ by Pratyusha Sharma, et al. ∙ 0 ∙ share

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Self-Supervised Exploration via Disagreement

Efficient exploration is a long-standing problem in sensorimotor learnin...
06/10/2019 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Image Inpainting

Fills holes in images

05/17/2019 Deepak Pathak ∙ 30 ∙ share

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Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity

Contemporary sensorimotor learning approaches typically start with an ex...
02/14/2019 ∙ by Deepak Pathak, et al. ∙ 12 ∙ share

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Large-Scale Study of Curiosity-Driven Learning

Reinforcement learning algorithms rely on carefully engineering environm...
08/13/2018 ∙ by Yuri Burda, et al. ∙ 0 ∙ share

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Compositional GAN: Learning Conditional Image Composition

Generative Adversarial Networks (GANs) can produce images of surprising ...
07/19/2018 ∙ by Samaneh Azadi, et al. ∙ 16 ∙ share

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Learning Instance Segmentation by Interaction

We present an approach for building an active agent that learns to segme...
06/21/2018 ∙ by Deepak Pathak, et al. ∙ 2 ∙ share

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Zero-Shot Visual Imitation

The current dominant paradigm for imitation learning relies on strong su...
04/23/2018 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Investigating Human Priors for Playing Video Games

What makes humans so good at solving seemingly complex video games? Unli...
02/28/2018 ∙ by Rachit Dubey, et al. ∙ 0 ∙ share

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Toward Multimodal Image-to-Image Translation

Many image-to-image translation problems are ambiguous, as a single inpu...
11/30/2017 ∙ by Jun-Yan Zhu, et al. ∙ 0 ∙ share

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Curiosity-driven Exploration by Self-supervised Prediction

In many real-world scenarios, rewards extrinsic to the agent are extreme...
05/15/2017 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Learning Features by Watching Objects Move

This paper presents a novel yet intuitive approach to unsupervised featu...
12/19/2016 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Context Encoders: Feature Learning by Inpainting

We present an unsupervised visual feature learning algorithm driven by c...
04/25/2016 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

We present an approach to learn a dense pixel-wise labeling from image-l...
06/11/2015 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Fully Convolutional Multi-Class Multiple Instance Learning

Multiple instance learning (MIL) can reduce the need for costly annotati...
12/22/2014 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning

We develop methods for detector learning which exploit joint training ov...
12/02/2014 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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Deepak Pathak

Featured Co-authors

Sergey Levine

Pieter Abbeel

Trevor Darrell

Kate Saenko

Jitendra Malik

Abhinav Gupta

Ross Girshick

Kostas Daniilidis

Alexei A. Efros

Thomas L. Griffiths

Manmohan Chandraker

RMA: Rapid Motor Adaptation for Legged Robots

Auto-Tuned Sim-to-Real Transfer

Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image

FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation

Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion

Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control

Locally Masked Convolution for Autoregressive Models

Planning to Explore via Self-Supervised World Models

Sparse Graphical Memory for Robust Planning

Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller

Self-Supervised Exploration via Disagreement

Image Inpainting

Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity

Large-Scale Study of Curiosity-Driven Learning

Compositional GAN: Learning Conditional Image Composition

Learning Instance Segmentation by Interaction

Zero-Shot Visual Imitation

Investigating Human Priors for Playing Video Games

Toward Multimodal Image-to-Image Translation

Curiosity-driven Exploration by Self-supervised Prediction

Learning Features by Watching Objects Move

Context Encoders: Feature Learning by Inpainting

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

Fully Convolutional Multi-Class Multiple Instance Learning

Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning