Facial Expression Recognition On Ferplus
Metrics
Accuracy(pretrained)
Results
Performance results of various models on this benchmark
Model Name | Accuracy(pretrained) | Paper Title | Repository |
|---|---|---|---|
| RAN (VGG-16) | 89.16 | Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition | |
| KTN | 90.49 | Adaptively Learning Facial Expression Representation via C-F Labels and Distillation | - |
| Local Learning Deep + BOW | 87.76 | Local Learning with Deep and Handcrafted Features for Facial Expression Recognition | - |
| SENet Teacher | 88.88 | Emotion Recognition in Speech using Cross-Modal Transfer in the Wild | - |
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