Multi-task face analyses through adversarial learning

•We propose an adversarial learning method to capture multi-task dependencies from both representation-level and label-level.•We design a recognizer and a discriminator for multi-task face analyses.•Experimental results on benchmark datasets demonstrate the superiority of the proposed method to state of the art.