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Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face Manipulation" published in CVPR 2020.

See the MSU CVLab website for project details and access to the DFFD dataset.

http://cvlab.cse.msu.edu/project-ffd.html

This code is provided as example code, and may not reflect a specific combination of hyper-parameters presented in the paper.

• xception.py: Defines the Xception network with the attention mechanism
• train*.py: Train the model on the train data
• test*.py: Evaluate the model on the test data

If you use or refer to this source code, please cite the following paper:

@inproceedings{cvpr2020-dang,
  title={On the Detection of Digital Face Manipulation},
  author={Hao Dang, Feng Liu, Joel Stehouwer, Xiaoming Liu, Anil Jain},
  booktitle={In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020)},
  address={Seattle, WA},
  year={2020}
}