Edoardo Daniele Cannas

Hey @IItaly , > The real scores are greater than 1. That's OK, as the networks output the unnormalized scores of deepfake detection. If you want a 0-1 probabilistic value,...

Hey @IItaly , let me see if I have understood everything straight: 1. you have tried to load the pre-trained model we provide, and it worked; 2. you have tried...

Hey @IItaly , yes that is definitely curious! If you used directly the train_all.sh, you should get close numbers to the ones of the paper. I'm wondering if the pre-trained...

Hey @IItaly , When you call len() on a DataLoader it should return the result of calling len() on the dataset of the loader. Can you please share the list...

Hey @IItaly , I see you have pytorch=1.3.1, while in our experiments we use pytorch=1.4.0. To avoid similar issues in the future, I suggest you to create a separate environment...

Hey @IItaly , we noticed just now that in the `train_all.sh` script we set as number of iterations 30000. In the original paper instead we used 20000 iterations, and from...

Hey @IItaly , if you are referring to the [Analyze results notebook](https://github.com/polimi-ispl/icpr2020dfdc/blob/master/notebook/Analyze%20results.ipynb) you are right, in the `compute_metrics` function before computing the ROC curve we should apply a sigmoid to...

Hey @IItaly , > Thank you for your reply. Maybe that's why I got a higher score than that reported in your paper？ it might be, did you manage to...

> Yes.I want to get the correct AUC value. Then yes, you should mean the score for all frames for each video, and the normalize between 0 and 1 with...

Hey @IItaly , you're right, you shouldn't need it. Just try doing `expit(df['score'])` as you should already have the mean of scores for each vide thanks to the group by...