What is the difference between BatchNorm and Adaptive BatchNorm (AdaBN)?
I think the original batch normalization paper proposes to use mean and standard deviation estimated on the train set. The adaptive batch normalization simply re-estimates them on the target domain (could be the test set, or some unlabeled data from the target domain). 

Please correct me if I am wrong.