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 | ResEmoteNet | Overall Accuracy | 94.76 | — | Unverified |
| 2 | FMAE | Overall Accuracy | 93.45 | — | Unverified |
| 3 | QCS | Overall Accuracy | 93.02 | — | Unverified |
| 4 | Norface | Overall Accuracy | 92.97 | — | Unverified |
| 5 | S2D | Overall Accuracy | 92.57 | — | Unverified |
| 6 | BTN | Overall Accuracy | 92.54 | — | Unverified |
| 7 | GReFEL | Overall Accuracy | 92.47 | — | Unverified |
| 8 | DDAMFN++ | Overall Accuracy | 92.34 | — | Unverified |
| 9 | DCJT | Overall Accuracy | 92.24 | — | Unverified |
| 10 | POSTER++ | Overall Accuracy | 92.21 | — | Unverified |