Facial Expression Recognition on JAFFE
98AccuracyKhaireddin
Evaluation results
| Method | Links | ||
|---|---|---|---|
| KhaireddinModel=CNN2026.05 | 98 | — | |
| POSTER2023.05 | 96.67 | — | |
| POSTER++2023.05 | 96.67 | — | |
| ARBEx2023.05 | 96.67 | — | |
| PCNN2025.12 | 96.49 | — | |
| [3]Year=2020, Model Type=Handcrafted, Evaluation Protocol=10-fold cross validation2021.07 | 96 | — | |
| Poster2025.12 | 94.57 | — | |
| ViT + SEModel Type=Deep Learning, Evaluation Protocol=10-fold cross validation2021.07 | 92.92 | — | |
| [38]Year=2021, Model Type=Deep Learning, Evaluation Protocol=10-fold cross validation2021.07 | 92.8 | — | |
| RUL2023.05 | 92.33 | — | |
| EfficientFace2023.05 | 92.33 | — | |
| RUL2025.12 | 92.33 | — | |
| EfficientFace2025.12 | 92.33 | — | |
| [39]Year=2015, Model Type=Handcrafted, Evaluation Protocol=10-fold cross validation2021.07 | 91.8 | — | |
| RAN2023.05 | 88.67 | — | |
| RAN2025.12 | 88.67 | — | |
| DachapallyModel=Autoencoder2026.05 | 86.38 | — | |
| SCN2023.05 | 86.33 | — | |
| SCN2025.12 | 86.33 | — | |
| DFASource set=CK+, Backbone=Manually designed network2020.08 | 63.38 | — | |
| ECANSource set=RAF-DB 2.0, Backbone=VGGNet2020.08 | 61.94 | — | |
| AGRASource set=RAF-DB, Backbone=ResNet-502020.08 | 61.5 | — | |
| SAFNSource set=RAF-DB, Backbone=ResNet-502020.08 | 61.03 | — | |
| DETNSource set=RAF-DB, Backbone=Manually designed network2020.08 | 57.75 | — | |
| ECANSource set=RAF-DB, Backbone=ResNet-502020.08 | 57.28 | — | |
| DETNSource set=RAF-DB, Backbone=ResNet-502020.08 | 55.89 | — | |
| SWDSource set=RAF-DB, Backbone=ResNet-502020.08 | 54.93 | — | |
| JUMBOTSource set=RAF-DB, Backbone=ResNet-502020.08 | 54.13 | — | |
| PLFTSource set=RAF-DB, Backbone=ResNet-502020.08 | 53.99 | — | |
| LPLSource set=RAF-DB, Backbone=ResNet-502020.08 | 53.05 | — | |
| FTDNNSource set=RAF-DB, Backbone=ResNet-502020.08 | 52.11 | — | |
| CADASource set=RAF-DB, Backbone=ResNet-502020.08 | 52.11 | — | |
| ETDSource set=RAF-DB, Backbone=ResNet-502020.08 | 51.19 | — | |
| ICIDSource set=RAF-DB, Backbone=ResNet-502020.08 | 50.7 | — | |
| DTSource set=RAF-DB, Backbone=ResNet-502020.08 | 50.23 | — | |
| DFASource set=RAF-DB, Backbone=ResNet-502020.08 | 44.44 | — | |
| FTDNNSource set=Six datasets, Backbone=VGGNet2020.08 | 44.32 | — | |
| Da et al.Source set=BOSPHORUS, Backbone=HOG & Gabor filters2020.08 | 36.2 | — | |
| AGRABackbone=ResNet502025.12 | — | 61.5 | |
| CSRLBackbone=ResNet182025.12 | — | 66.67 | |
| ECANBackbone=ResNet502025.12 | — | 57.28 | |
| MotivNetBackbone=ViT2025.12 | — | 58.57 |