Importance-Weighted Conditional Adversarial Network for Unsupervised Domain Adaptation

•Propose a deep adversarial adaptation network for unsupervised domain adaptation(DA).•The network contributes to reducing the harmful impact of hard-to-transfer samples.•Derive a new sample selection criterion to improve target domain discriminability.•Extensive experimentation shows its effectiveness over previous DA methods.