Facial Expression Recognition (FER)
Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face such as eyebrows, eyes, mouth, and other features, and mapping them to a set of emotions such as anger, fear, surprise, sadness and happiness.
( Image credit: DeXpression )
Papers
Showing 1–10 of 492 papers
All datasetsAffectNetRAF-DBFER2013FER+Acted Facial Expressions In The Wild (AFEW)CK+FERPlusJAFFESFEWAff-Wild2BP4DDISFA
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | PAtt-Lite | Accuracy (7 emotion) | 100 | — | Unverified |
| 2 | EmoNeXt | Accuracy (8 emotion) | 100 | — | Unverified |
| 3 | ViT + SE | Accuracy (7 emotion) | 99.8 | — | Unverified |
| 4 | FAN | Accuracy (7 emotion) | 99.7 | — | Unverified |
| 5 | Nonlinear eval on SL + SSL puzzling (B0) | Accuracy (7 emotion) | 98.23 | — | Unverified |
| 6 | DeepEmotion | Accuracy (7 emotion) | 98 | — | Unverified |
| 7 | FN2EN | Accuracy (8 emotion) | 96.8 | — | Unverified |