Comments (1)
Hi,
CAT-Net is the first work to use DCT coefficients in CNN for forgery localization. While there have been follow-up works that have used DCT coefficients, as far as I know, none of them address the problem of removal forgeries.
It is unclear whether this model is effective in detecting removal forgeries or if modifications are necessary.
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Related Issues (20)
- Generalization on new data! HOT 3
- Identifying type of tampering HOT 1
- How should I set the threshold for inference? HOT 1
- insufficient shared memory in training phase HOT 3
- When inference, do I need to convert image to jpg format first? HOT 3
- A question about the dataset and train HOT 3
- About JPEGIO HOT 1
- F1 score HOT 1
- Can you tell me why my output is red when I train? HOT 1
- About training dataset 'Fantastic Reality' HOT 9
- about infer.py HOT 4
- torch 1.1.0 HOT 1
- cannot load DCT HOT 1
- fine tune with custom data HOT 1
- pretrained DCT of training HOT 1
- fusion part HOT 2
- can i use new arch? HOT 1
- About validate performance HOT 1
- invalid device id error while running tools/infer.py HOT 1
- Transfer learning on a large dataset HOT 4
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from cat-net.