A method for performing video domain adaptation for human action recognition is presented. The method includes using (701) annotated source data from a source video and unannotated target data from a target video in an unsupervised domain adaptation setting, identifying and aligning (703) discriminative clips in the source and target videos via an attention mechanism, and learning (705) spatial-background invariant human action representations by employing a self-supervised clip order prediction loss for both the annotated source data and the unannotated target data.
SHUFFLE, ATTEND, AND ADAPT: VIDEO DOMAIN ADAPTATION BY CLIP ORDER PREDICTION AND CLIP ATTENTION ALIGNMENT