Domain-Symmetric Networks for Adversarial Domain Adaptation
Domain-Symmetric Networks for Adversarial Domain Adaptation
Unsupervised domain adaptation aims to learn a model of classifier for unlabeled samples on the target domain, given training data of labeled samples on the source domain. Impressive progress is made recently by learning invariant features via domain-adversarial training of deep networks. In spite of the recent progress, domain adaptation …