Deepak Pathak

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berkeley college

Deepak Pathak is a PhD student focused on computer vision and machine learning.

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 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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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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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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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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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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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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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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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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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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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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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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Deepak Pathak

Featured Co-authors

Sergey Levine

Trevor Darrell

Jitendra Malik

Abhinav Gupta

Kate Saenko

Ross Girshick

Alexei A. Efros

Thomas L. Griffiths

Amos Storkey

Eli Shechtman

Piotr Dollár

Compositional GAN: Learning Conditional Image Composition

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

Learning Instance Segmentation by Interaction

Curiosity-driven Exploration by Self-supervised Prediction

Learning Features by Watching Objects Move

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

Context Encoders: Feature Learning by Inpainting

Toward Multimodal Image-to-Image Translation

Investigating Human Priors for Playing Video Games

Zero-Shot Visual Imitation

Large-Scale Study of Curiosity-Driven Learning

Self-Supervised Exploration via Disagreement

Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller