Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition

Understand

Automated emotion recognition in the wild from facial images remains a challenging problem.

• Although recent advances in Deep Learning have supposed a significant breakthrough in this topic, strong changes in pose, orientation and point of view severely harm current approaches.
• In addition, the acquisition of labeled datasets is costly, and current state-of-the-art deep learning algorithms cannot model all the aforementioned difficulties.
• In this paper, we propose to apply a multi-task learning loss function to share a common feature representation with other related tasks.