Trevor Darrell

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berkeley college

Professor at University of California, Berkeley

Semantic Bottleneck Scene Generation

Coupling the high-fidelity generation capabilities of label-conditional ...
11/26/2019 ∙ by Samaneh Azadi, et al. ∙ 33 ∙ share

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Revisiting Few-shot Activity Detection with Class Similarity Control

Many interesting events in the real world are rare making preannotated m...
03/31/2020 ∙ by Huijuan Xu, et al. ∙ 28 ∙ share

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Modular Architecture for StarCraft II with Deep Reinforcement Learning

We present a novel modular architecture for StarCraft II AI. The archite...
11/08/2018 ∙ by Dennis Lee, et al. ∙ 24 ∙ share

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Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning

Learning robotic manipulation tasks using reinforcement learning with sp...
12/23/2019 ∙ by Richard Li, et al. ∙ 23 ∙ share

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Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

Many visual scenes contain text that carries crucial information, and it...
11/14/2019 ∙ by Ronghang Hu, et al. ∙ 22 ∙ share

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Regularization Matters in Policy Optimization

Deep Reinforcement Learning (Deep RL) has been receiving increasingly mo...
10/21/2019 ∙ by Zhuang Liu, et al. ∙ 21 ∙ share

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Unsupervised Domain Adaptation through Self-Supervision

This paper addresses unsupervised domain adaptation, the setting where l...
09/26/2019 ∙ by Yu Sun, et al. ∙ 18 ∙ 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 Canonical Representations for Scene Graph to Image Generation

Generating realistic images of complex visual scenes becomes very challe...
12/16/2019 ∙ by Roei Herzig, et al. ∙ 15 ∙ share

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Adversarial Inference for Multi-Sentence Video Description

While significant progress has been made in the image captioning task, v...
12/13/2018 ∙ by Jae Sung Park, et al. ∙ 14 ∙ share

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Spatio-Temporal Action Detection with Multi-Object Interaction

Spatio-temporal action detection in videos requires localizing the actio...
04/01/2020 ∙ by Huijuan Xu, et al. ∙ 13 ∙ 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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Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control

Autonomous agents situated in real-world environments must be able to ma...
10/30/2019 ∙ by Coline Devin, et al. ∙ 12 ∙ share

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Something-Else: Compositional Action Recognition with Spatial-Temporal Interaction Networks

Human action is naturally compositional: humans can easily recognize and...
12/20/2019 ∙ by Joanna Materzyńska, et al. ∙ 12 ∙ share

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A New Meta-Baseline for Few-Shot Learning

Meta-learning has become a popular framework for few-shot learning in re...
03/09/2020 ∙ by Yinbo Chen, et al. ∙ 11 ∙ share

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Frustratingly Simple Few-Shot Object Detection

Detecting rare objects from a few examples is an emerging problem. Prior...
03/16/2020 ∙ by Xin Wang, et al. ∙ 10 ∙ share

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Scoring-Aggregating-Planning: Learning task-agnostic priors from interactions and sparse rewards for zero-shot generalization

Humans can learn task-agnostic priors from interactive experience and ut...
10/17/2019 ∙ by Huazhe Xu, et al. ∙ 8 ∙ share

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Rethinking Image Mixture for Unsupervised Visual Representation Learning

In supervised learning, smoothing label/prediction distribution in neura...
03/11/2020 ∙ by Zhiqiang Shen, et al. ∙ 8 ∙ share

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Adversarial Continual Learning

Continual learning aims to learn new tasks without forgetting previously...
03/21/2020 ∙ by Sayna Ebrahimi, et al. ∙ 8 ∙ share

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Viewpoint Invariant Change Captioning

The ability to detect that something has changed in an environment is va...
01/08/2019 ∙ by Dong Huk Park, et al. ∙ 6 ∙ share

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Semi-supervised Domain Adaptation via Minimax Entropy

Contemporary domain adaptation methods are very effective at aligning fe...
04/13/2019 ∙ by Kuniaki Saito, et al. ∙ 6 ∙ share

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Language-Conditioned Graph Networks for Relational Reasoning

Solving grounded language tasks often requires reasoning about relations...
05/10/2019 ∙ by Ronghang Hu, et al. ∙ 6 ∙ share

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Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning

Weakly-supervised action localization problem requires training a model ...
03/31/2020 ∙ by Zhekun Luo, et al. ∙ 5 ∙ share

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Similarity R-C3D for Few-shot Temporal Activity Detection

Many activities of interest are rare events, with only a few labeled exa...
12/25/2018 ∙ by Huijuan Xu, et al. ∙ 4 ∙ share

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BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling

Datasets drive vision progress and autonomous driving is a critical visi...
05/12/2018 ∙ by Fisher Yu, et al. ∙ 2 ∙ share

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Textual Explanations for Self-Driving Vehicles

Deep neural perception and control networks have become key components o...
07/30/2018 ∙ by Jinkyu Kim, et al. ∙ 2 ∙ 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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Localizing Moments in Video with Temporal Language

Localizing moments in a longer video via natural language queries is a n...
09/05/2018 ∙ by Lisa Anne Hendricks, et al. ∙ 2 ∙ share

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Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Deep models that are both effective and explainable are desirable in man...
02/15/2018 ∙ by Dong Huk Park, et al. ∙ 1 ∙ share

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Generating Counterfactual Explanations with Natural Language

Natural language explanations of deep neural network decisions provide a...
06/26/2018 ∙ by Lisa Anne Hendricks, et al. ∙ 1 ∙ share

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Multi-Content GAN for Few-Shot Font Style Transfer

In this work, we focus on the challenge of taking partial observations o...
12/01/2017 ∙ by Samaneh Azadi, et al. ∙ 0 ∙ share

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Learning to Segment Every Thing

Existing methods for object instance segmentation require all training i...
11/28/2017 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)

Deep models are the defacto standard in visual decision problems due to ...
11/17/2017 ∙ by Dong Huk Park, et al. ∙ 0 ∙ share

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Grounding Visual Explanations (Extended Abstract)

Existing models which generate textual explanations enforce task relevan...
11/17/2017 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Domain adaptation is critical for success in new, unseen environments. A...
11/08/2017 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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Gradient-free Policy Architecture Search and Adaptation

We develop a method for policy architecture search and adaptation via gr...
10/16/2017 ∙ by Sayna Ebrahimi, et al. ∙ 0 ∙ share

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Deep Object-Centric Representations for Generalizable Robot Learning

Robotic manipulation in complex open-world scenarios requires both relia...
08/14/2017 ∙ by Coline Devin, et al. ∙ 0 ∙ share

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Localizing Moments in Video with Natural Language

We consider retrieving a specific temporal segment, or moment, from a vi...
08/04/2017 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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Deep Layer Aggregation

Convolutional networks have had great success in image classification an...
07/20/2017 ∙ by Fisher Yu, 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 Detection with Diverse Proposals

To predict a set of diverse and informative proposals with enriched repr...
04/11/2017 ∙ by Samaneh Azadi, 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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FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

Fully convolutional models for dense prediction have proven successful f...
12/08/2016 ∙ by Judy Hoffman, et al. ∙ 0 ∙ share

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End-to-end Learning of Driving Models from Large-scale Video Datasets

Robust perception-action models should be learned from training data wit...
12/04/2016 ∙ by Huazhe Xu, et al. ∙ 0 ∙ share

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Modeling Relationships in Referential Expressions with Compositional Modular Networks

People often refer to entities in an image in terms of their relationshi...
11/30/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions

Image segmentation from referring expressions is a joint vision and lang...
08/30/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Clockwork Convnets for Video Semantic Segmentation

Recent years have seen tremendous progress in still-image segmentation; ...
08/11/2016 ∙ by Evan Shelhamer, et al. ∙ 0 ∙ share

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Adversarial Feature Learning

The ability of the Generative Adversarial Networks (GANs) framework to l...
05/31/2016 ∙ by Jeff Donahue, et al. ∙ 0 ∙ share

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Fully Convolutional Networks for Semantic Segmentation

Convolutional networks are powerful visual models that yield hierarchies...
05/20/2016 ∙ by Evan Shelhamer, et al. ∙ 0 ∙ share

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Segmentation from Natural Language Expressions

In this paper we approach the novel problem of segmenting an image based...
03/20/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Trevor Darrell

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