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Proactive Image Manipulation Detection

Official Pytorch implementation of CVPR 2022 paper "Proactive Image Manipulation Detection ".

Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu

The paper and supplementary can be found at:

alt text

Prerequisites

  • PyTorch 1.5.0
  • Numpy 1.14.2
  • Scikit-learn 0.22.2

Getting Started

Datasets

Pre-trained model

The pre-trained model trained on STGAN can be downloaded from: https://drive.google.com/file/d/1p9zETa9rCU0wx8wD5Ige2TbCL8WciV7o/view?usp=sharing

Training

  • Go to the folder STGAN
  • Download the STGAN repository files and pre-trained model from https://github.com/csmliu/STGAN
  • Provide the train and test path in respective codes as sepecified below.
  • Provide the model path to resume training
  • Run the code as shown below:
python train.py

Testing using pre-trained models

python test_stargan.py
  • Run the code as shown below for CycleGAN:
python test_cyclegan.py
  • Run the code as shown below for GauGAN:
python test_gaugan.py

If you would like to use our work, please cite:

@inproceedings{asnani2022proactive
      title={Proactive Image Manipulation Detection}, 
      author={Asnani, Vishal and Yin, Xi and Hassner, Tal and Liu, Sijia and Liu, Xiaoming},
      booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
      year={2022}
      
}

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