Pose-adaptive Hierarchical Attention Network for Facial Expression Recognition

Understand

Multi-view facial expression recognition (FER) is a challenging task because the appearance of an expression varies in poses.

• To alleviate the influences of poses, recent methods either perform pose normalization or learn separate FER classifiers for each pose.
• However, these methods usually have two stages and rely on good performance of pose estimators.
• Different from existing methods, we propose a pose-adaptive hierarchical attention network (PhaNet) that can jointly recognize the facial expressions and poses in unconstrained environment.