  One of the most universal ways that people communicate is through facial
expressions. In this paper, we take a deep dive, implementing multiple deep
learning models for facial expression recognition (FER). Our goals are twofold:
we aim not only to maximize accuracy, but also to apply our results to the
real-world. By leveraging numerous techniques from recent research, we
demonstrate a state-of-the-art 75.8% accuracy on the FER2013 test set,
outperforming all existing publications. Additionally, we showcase a mobile web
app which runs our FER models on-device in real time.
