CADDM-Implicit_Identity_Leakage: A C++ repository from pandalandala

Dependencies

Python 3 >= 3.6
Pytorch >= 1.6.0
OpenCV >= 4.4.0
Scipy >= 1.4.1
NumPy >= 1.19.5

Data Preparation

Take FF++ as an example:

Download the dataset from FF++ and put them under the ./data.

.
└── data
    └── FaceForensics++
        ├── original_sequences
        │   └── youtube
        │       └── raw
        │           └── videos
        │               └── *.mp4
        ├── manipulated_sequences
        │   ├── Deepfakes
        │       └── raw
        │           └── videos
        │               └── *.mp4
        │   ├── Face2Face
        │		...
        │   ├── FaceSwap
        │		...
        │   ├── NeuralTextures
        │		...
        │   ├── FaceShifter
        │		...

Download the landmark detector from here and put it in the folder ./lib.
Run the code to extract frames from FF++ videos and save them under the ./train_images or ./test_images based on the division in the original dataset.
```
 python lib/extract_frames_ldm_ff++.py
```

Pretrained weights

You can download pretrained weights here.

Evaluations

To evaluate the model performance, please run:

python test.py   --cfg ./configs/caddm_test.cfg

Results

Our model achieved the following performance on:

Training Data	Backbone	FF++	Celeb-DF	DFDC
FF++	ResNet-34	99.70%	91.15%	71.49%
FF++	EfficientNet-b3	99.78%	93.08%	73.34%
FF++	EfficientNet-b4	99.79%	93.88%	73.85%

Note: the metric is video-level AUC.

Training

To train our model from scratch, please run :

python  train.py --cfg ./configs/caddm_train.cfg