Facial Expression Recognition using Squeeze and Excitation-powered Swin Transformers

We present a facial emotion recognition framework, built upon Swin vision Transformers jointly with squeeze and excitation block (SE). A transformer model based on an attention mechanism has been presented recently to address vision tasks. Our method uses a vision transformer with a Squeeze excitation block (SE) and sharpness-aware minimizer (SAM). We have used a hybrid dataset, to train our model and the AffectNet dataset to evaluate the result of our model