deyanlazarov / FDFtNet

FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network. (IFIP-SEC 2020)

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FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network.

Hyeonseong Jeon, Youngoh Bang, and Simon S. Woo.

(1) Setup

Install packages

• pip install -r requirements.txt

(2) Datasets

The dataset in the paper can be downloaded here.

• Deepfake: https://github.com/ondyari/FaceForensics
• Face2Face: https://github.com/ondyari/FaceForensics
• PGGAN dataset is not disclosed at the request of the dataset source.

Original dataset of the Deepfake, Face2Face can also be downloaded from FaceForensics

Preprocessing

Will be uploaded soon...

# Crop the face parts to image from the videos by frame
cd dataset
# using MTCNN [1]
python preprocess_dataset.py -d youtube

python preprocess_dataset.py
 -d <dataset type, e.g., youtube, Deepfakes, Face2Face>

(3) Models

• SqueezeNet
• ResNetV2
• Xception
• ShallowNetV3 is not disclosed at the request of the model source.

(4) Quick-start

(5) Pre-train

(6) Fine-tune

(7) Evaluate

References

[1] Zhang, K., Zhang, Z., Li, Z., and Qiao, Y. (2016). Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters, 23(10):1499–1503.