shruti-shyam / dsp-fwa Goto Github PK

We propose an improved version of our previous work "Exposing DeepFake Videos By Detecting Face Warping Artifacts". We employ a dual spatial pyramid strategy on both image and feature level to tackle multi-scale issues.

• PyTorch 1.0.1
• Ubuntu >= 16.04
• CUDA >= 8.0
• Python3 with packages opencv3 and dlib

Check demo.py in toy fodler. This script will return a list that contains the "fake" probability of each input data. Note we only suppert ResNet-50 based SSPNet model in this version. The checkpoint can be downloaded here.

    python demo.py \
    --arch=sppnet \
    --layers=50 \
    --save_dir=../ckpt/ \
    --input=/path/of/video_or_image \
    --ckpt_name=SPP-res50.pth

Please cite this paper in your publications if this repository helps your research:

@inproceedings{li2019exposing,
  title={Exposing DeepFake Videos By Detecting Face Warping Artifacts},
  author={Li, Yuezun and Lyu, Siwei},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2019}
}

This repository is NOT for commecial use. It is provided "as it is" and we are not responsible for any subsequence of using this code.