Adversarial Discriminative Domain Adaptation

Adversarial learning methods are a promising approach to training robust deep networks, and can generate complex samples across diverse domains. They can also improve recognition despite the presence of domain shift or dataset bias: recent adversarial approaches to unsupervised domain adaptation red...

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Bibliographic Details
Main Authors: Tzeng, Eric, Hoffman, Judy, Saenko, Kate, Darrell, Trevor
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
Gallium nitride
Image reconstruction
Training
Visualization
Online Access:Request full text
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