Judy Hoffman

According to our database1, Judy Hoffman authored at least 50 papers between 2011 and 2018.

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Bibliography

2018
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation.
CoRR, 2018

Algorithms and Theory for Multiple-Source Adaptation.
CoRR, 2018

Scaling Human-Object Interaction Recognition Through Zero-Shot Learning.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

CyCADA: Cycle-Consistent Adversarial Domain Adaptation.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Simultaneous Deep Transfer Across Domains and Tasks.
Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Label Efficient Learning of Transferable Representations across Domains and Tasks.
CoRR, 2017

Multiple-Source Adaptation for Regression Problems.
CoRR, 2017

CyCADA: Cycle-Consistent Adversarial Domain Adaptation.
CoRR, 2017

VisDA: The Visual Domain Adaptation Challenge.
CoRR, 2017

Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach.
CoRR, 2017

Adversarial Discriminative Domain Adaptation.
CoRR, 2017

Inferring and Executing Programs for Visual Reasoning.
CoRR, 2017

Label Efficient Learning of Transferable Representations acrosss Domains and Tasks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Inferring and Executing Programs for Visual Reasoning.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Fine-Grained Recognition in the Wild: A Multi-task Domain Adaptation Approach.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Adversarial Discriminative Domain Adaptation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning.
Journal of Machine Learning Research, 2016

Clockwork Convnets for Video Semantic Segmentation.
CoRR, 2016

Fine-to-coarse Knowledge Transfer For Low-Res Image Classification.
CoRR, 2016

FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation.
CoRR, 2016

Cross-modal adaptation for RGB-D detection.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Fine-to-coarse knowledge transfer for low-res image classification.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Clockwork Convnets for Video Semantic Segmentation.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Best Practices for Fine-Tuning Visual Classifiers to New Domains.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Learning with Side Information through Modality Hallucination.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Cross Modal Distillation for Supervision Transfer.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Simultaneous Deep Transfer Across Domains and Tasks.
CoRR, 2015

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments.
CoRR, 2015

Spatial Semantic Regularisation for Large Scale Object Detection.
CoRR, 2015

Cross Modal Distillation for Supervision Transfer.
CoRR, 2015

Quantification in-the-wild: data-sets and baselines.
CoRR, 2015

Simultaneous Deep Transfer Across Domains and Tasks.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Spatial Semantic Regularisation for Large Scale Object Detection.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Detector discovery in the wild: Joint multiple instance and representation learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Asymmetric and Category Invariant Feature Transformations for Domain Adaptation.
International Journal of Computer Vision, 2014

Deep Domain Confusion: Maximizing for Domain Invariance.
CoRR, 2014

Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning.
CoRR, 2014

LSDA: Large Scale Detection Through Adaptation.
CoRR, 2014

LSDA: Large Scale Detection through Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Interactive adaptation of real-time object detectors.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.
Proceedings of the 31th International Conference on Machine Learning, 2014

Continuous Manifold Based Adaptation for Evolving Visual Domains.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Efficient Learning of Domain-invariant Image Representations
CoRR, 2013

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations.
CoRR, 2013

One-Shot Adaptation of Supervised Deep Convolutional Models.
CoRR, 2013

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.
CoRR, 2013

Semi-supervised Domain Adaptation with Instance Constraints.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Discovering Latent Domains for Multisource Domain Adaptation.
Proceedings of the Computer Vision - ECCV 2012, 2012

Weakly Supervised Learning of Object Segmentations from Web-Scale Video.
Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

2011
EG-RRT: Environment-guided random trees for kinodynamic motion planning with uncertainty and obstacles.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011


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