Emotion Recognition on AffectNet 8 classes (test val)
62.42AccuracyEfficientNet-B2
Evaluation results
| Method | Links | |
|---|---|---|
| EfficientNet-B2Pre-training Dataset=VGGFace22021.03 | 62.42 | |
| DAN2021.03 | 62.09 | |
| Distilled student2021.03 | 61.6 | |
| ARMBackbone=ResNet-182021.03 | 61.33 | |
| EfficientNet-B0Pre-training Dataset=VGGFace22021.03 | 61.32 | |
| PSRBackbone=VGG-162021.03 | 60.68 | |
| EfficientNet-B2Pre-training Dataset=ImageNet2021.03 | 60.28 | |
| MobileNet-v1Pre-training Dataset=VGGFace22021.03 | 60.2 | |
| Inception-v3Pre-training Dataset=ImageNet2021.03 | 59.65 | |
| RAN2021.03 | 59.5 | |
| Ensemble with Shared Representations2021.03 | 59.3 | |
| SENet-50Pre-training Dataset=VGGFace22021.03 | 58.7 | |
| NFNet-F0Pre-training Dataset=ImageNet2021.03 | 58.35 | |
| Weighted-LossBackbone=AlexNet2021.03 | 58 | |
| EfficientNet-B0Pre-training Dataset=ImageNet2021.03 | 57.55 | |
| MobileNet-v1Pre-training Dataset=ImageNet2021.03 | 56.88 | |
| Pre-trained EfficientNet-B0Pre-training Dataset=VGGFace2, Status=Frozen/No Fine-tuning2021.03 | 49.15 | |
| Pre-trained RexNet-150Pre-training Dataset=VGGFace2, Status=Frozen/No Fine-tuning2021.03 | 48.88 | |
| Pre-trained SENet-50Pre-training Dataset=VGGFace2, Status=Frozen/No Fine-tuning2021.03 | 40.87 | |
| Pre-trained MobileNet-v1Pre-training Dataset=VGGFace2, Status=Frozen/No Fine-tuning2021.03 | 40.58 |