Learning Vision Transformer with Squeeze and Excitation for Facial Expression Recognition

Understand

As various databases of facial expressions have been made accessible over the last few decades, the Facial Expression Recognition (FER) task has gotten a lot of interest.

• The multiple sources of the available databases raised several challenges for facial recognition task.
• These challenges are usually addressed by Convolution Neural Network (CNN) architectures.
• Different from CNN models, a Transformer model based on attention mechanism has been presented recently to address vision tasks.