Comments (1)
nicobonne
commented on June 14, 2024
Well, that's a million dollar question 😉
Overfitting was a big problem in DFDC, and the fact that the training dataset was composed by a few actors surely didn't help.
Adding external data to the training set would have helped but we decided to keep only the original dataset to avoid the risk of being disqualified.
A way to reduce overfitting for the challenge was to split the original dataset into non overlapping subset and train several instances of the same model over those separated sets. You can find a little more in our Kaggle post.
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Related Issues (20)
- Facing error while running train_all.sh HOT 2
- Celebdf dataset HOT 1
- Can't find the file data_frame_df.pkl HOT 3
- network doesn't generalize well HOT 3
- Query HOT 4
- Unable to find "List_of_testing_videos.txt" HOT 1
- Source code of Ensemble models HOT 18
- index_dfdc errror HOT 2
- DFDC split HOT 1
- Question about the returned RuntimeError when using the Celeb-DF dataset HOT 7
- what is embedding_routine function used for? HOT 1
- how to set validation split for dfdc? HOT 4
- use pre-trained model to detect my videos, but filter out some specific datasets on the pre-train which may overlap HOT 2
- regarding attention heatmap HOT 1
- Training dataset for DFDC HOT 1
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- EnvironmentNameNotFound: Could not find conda environment: icpr2020 HOT 3
- About Image prediction notebook on Colab HOT 3
- val_sample HOT 1
- Regarding Top-up Training to improve the accuracy of existing deepfake model
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