Two-level Attention with Two-stage Multi-task Learning for Facial Emotion Recognition

Understand

Compared with facial emotion recognition on categorical model, the dimensional emotion recognition can describe numerous emotions of the real world more accurately.

• Most prior works of dimensional emotion estimation only considered laboratory data and used video, speech or other multi-modal features.
• The effect of these methods applied on static images in the real world is unknown.
• In this paper, a two-level attention with two-stage multi-task learning (2Att-2Mt) framework is proposed for facial emotion estimation on only static images.