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Hi @yihuacheng,
I trained your pre-trained model on MPIIFaceGaze. I haven't made any changes in the script for training as well as pre-processing of dataset. I performed the leave-one-person-out evaluation on this dataset as mentioned in your paper.
I am using PyTorch 1.7.0.
I got the following best angular errors for respective person:
Person
Best error
0
2.37
1
4.36
2
4.41
3
4.49
4
3.05
5
3.79
6
3.07
7
4.34
8
4.44
9
4.15
10
5.89
11
5.42
12
4.09
13
3.71
14
6.23
Mean
4.254
The mean of this best angular errors comes out to be 4.254, which is far away from the reported 4.00 error.
Please let me know if I am missing something over here. Also, help me to reproduce the reported results.
The text was updated successfully, but these errors were encountered:
@yihuacheng Thanks for sharing this. I was able to reproduce results using your ETH-XGaze pretrained model. But I am not able to reproduce results when I am training from scratch on ETH-XGaze. Please share the ETH-XGaze training parameters.
Hi @yihuacheng,
I trained your pre-trained model on MPIIFaceGaze. I haven't made any changes in the script for training as well as pre-processing of dataset. I performed the leave-one-person-out evaluation on this dataset as mentioned in your paper.
I am using PyTorch 1.7.0.
I got the following best angular errors for respective person:
The mean of this best angular errors comes out to be 4.254, which is far away from the reported 4.00 error.
Please let me know if I am missing something over here. Also, help me to reproduce the reported results.
The text was updated successfully, but these errors were encountered: