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 | 95.55 | — | Unverified |
| 2 | GReFEL | Accuracy | 93.09 | — | Unverified |
| 3 | QCS | Accuracy | 91.85 | — | Unverified |
| 4 | ResNet18 Dense Architecture | Accuracy | 91.41 | — | Unverified |
| 5 | DDAMFN | Accuracy | 90.74 | — | Unverified |
| 6 | KTN | Accuracy | 90.49 | — | Unverified |
| 7 | Vit-base + MAE | Accuracy | 90.18 | — | Unverified |
| 8 | FER-VT | Accuracy | 90.04 | — | Unverified |
| 9 | EAC | Accuracy | 89.64 | — | Unverified |
| 10 | LResNet50E-IR | Accuracy | 89.26 | — | Unverified |