Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

CVPR 2018 Kuniaki SaitoKohei WatanabeYoshitaka UshikuTatsuya Harada

In this work, we present a method for unsupervised domain adaptation. Many adversarial learning methods train domain classifier networks to distinguish the features as either a source or target and train a feature generator network to mimic the discriminator... (read more)

PDF Abstract

Evaluation Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.