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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:

Prerequisites

• PyTorch 1.5.0
• Numpy 1.14.2
• Scikit-learn 0.22.2

Getting Started

Datasets

• Every GM is used with different datasets they are trained on. Please refer to Table 2 of the supplementary for GM-dataset information. Download the dataset for the corressponding GMs from https://drive.google.com/file/d/1fAS7Sj3FhS6v31Z2hb9mp9gaGavgnLu5/view?usp=sharing
• The training data is used as CELEBA-HQ which is provided in the above link as CELEBA_HQ_TRAIN folder.

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

• Download the repository files and pre-trained model of GMs in the respective folder, StarGAN: https://github.com/yunjey/stargan , CycleGAN: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix , GauGAN: https://github.com/NVlabs/SPADE
• Download the pre-trained model for our template from https://drive.google.com/file/d/1p9zETa9rCU0wx8wD5Ige2TbCL8WciV7o/view?usp=sharing
• Provide the model path in the code
• Run the code as shown below for StarGAN:

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}
      
}