Facial Expression Recognition with Deep Learning
About
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.
Amil Khanzada, Charles Bai, Ferhat Turker Celepcikay• 2020
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Facial Expression Recognition | FER 2013 (test) | Accuracy Rate73.2 | 61 |
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