Spatial Transformer Networks are considered a powerful algorithm to learn the main areas of an image, but still, they could be more efficient by receiving images with embedded expert knowledge. This paper aims improve performance conventional Transformers when applied Facial Expression Recognition. Based on Transformers’ capacity spatial manipulation within networks, we propose different extens...

Facial Expression Recognition (FER) uses images of faces to identify the emotional state users, allowing for a closer interaction between humans and autonomous systems. Unfortunately, as naturally integrate some demographic information, such apparent age, gender, race subject, these systems are prone bias issues. In recent years, machine learning-based models have become most popular approach F...