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08/13/2020
Network Architecture Search for Domain Adaptation
Deep networks have been used to learn transferable representations for d...
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07/17/2020
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation
Conventional unsupervised domain adaptation (UDA) studies the knowledge ...
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12/10/2019
Learning Domain Adaptive Features with Unlabeled Domain Bridges
Conventional cross-domain image-to-image translation or unsupervised dom...
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11/05/2019
Federated Adversarial Domain Adaptation
Federated learning improves data privacy and efficiency in machine learn...
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10/23/2019
Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
Unsupervised knowledge transfer has a great potential to improve the gen...
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04/28/2019
Domain Agnostic Learning with Disentangled Representations
Unsupervised model transfer has the potential to greatly improve the gen...
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12/04/2018
Moment Matching for Multi-Source Domain Adaptation
Conventional unsupervised domain adaptation (UDA) assumes that training ...
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06/26/2018
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation
Unsupervised transfer of object recognition models from synthetic to rea...
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10/18/2017
VisDA: The Visual Domain Adaptation Challenge
We present the 2017 Visual Domain Adaptation (VisDA) dataset and challen...
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01/19/2017
Synthetic to Real Adaptation with Generative Correlation Alignment Networks
Synthetic images rendered from 3D CAD models are useful for augmenting t...
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09/14/2016
Combining Texture and Shape Cues for Object Recognition With Minimal Supervision
We present a novel approach to object classification and detection which...
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05/21/2016
Fine-to-coarse Knowledge Transfer For Low-Res Image Classification
We address the difficult problem of distinguishing fine-grained object c...
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04/09/2015
What Do Deep CNNs Learn About Objects?
Deep convolutional neural networks learn extremely powerful image repres...
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12/22/2014