Comments (2)
yaoing
commented on July 26, 2024
Thanks for your interest!
This MSCeleb-resnet18 pretrained model is not trained by myself. In fact, it's also used in many other FER works like SCN and DACL. However, the best performances of all these model are below your stated 88.75%.
If you're still unsure, try using their pre-trained MSCeleb-resnet18 model for training and use it as a reference.
from dan.
RockPine520
commented on July 26, 2024
Thanks for your advice. I'll try it.
from dan.
Related Issues (20)
- Wrong average accuracy report. HOT 2
- Why Batchnorm at the final network output? HOT 3
- Trained cluster centers HOT 3
- A mistake in rafdb.py HOT 2
- recommendation for program robustness HOT 1
- How to get 82.75% HOT 4
- Question about conversion of original Affectnet dataset HOT 2
- Some questions about the dataset HOT 1
- Re-produce the result. HOT 5
- Grad Cam visualization HOT 4
- Question in demo.py HOT 2
- Question in demo.py and run_grad_cam.py HOT 8
- MS-celeb预训练的下载地址无效
- feature vector
- 请问一下当运行rafdb.py时，在Affinity Loss中默认的num_classes为8类，可对于RAF_DB数据集而言只有7类，请问一下这8类如何解释呢 HOT 4
- GRADCAM++需要替换哪些变量 HOT 3
- 关于Grad_Cam
- Is this method also applicable for fer2013 data set? Why did the author not verify it on the most common fer2013 data set HOT 1
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