Facial Expression Recognition on FER Public 2013 (test)
72.05AccuracyVGG-VD-16
Evaluation results
| Method | Links | |
|---|---|---|
| VGG-VD-16Pretraining=VGGFaces2016.10 | 72.05 | |
| WuJie10102025.12 | 71.58 | |
| OCFER-NetBackbone=ResNet-182025.12 | 71.218 | |
| VGG-MPretraining=VGGFaces2016.10 | 71.08 | |
| AlexNetPretraining=VGGFaces2016.10 | 70.47 | |
| Resnet-50Pretraining=VGGFaces2016.10 | 69.23 | |
| Resnet-50Pretraining=ImageNet2016.10 | 67.79 | |
| VGG-VD-16Pretraining=ImageNet2016.10 | 66.92 | |
| VGG-MPretraining=ImageNet2016.10 | 66.04 | |
| AlexNetPretraining=ImageNet2016.10 | 62.44 |