Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning

Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning

Yuanhao Zhai, Tianyu Luan, David Doermann, Junsong Yuan

University at Buffalo

ICCV 2023

This repo contains the MIL-FCN version of our WSCL implementation.

1. Setup

Clone this repo

git clone git@github.com:yhZhai/WSCL.git

Install packages

pip install -r requirements.txt

2. Data preparation

We provide preprocessed CASIA (v1 and v2), Columbia, and Coverage datasets here. Place them under the data folder.

For other datasets, please prepare a json datalist file with similar structure as the existing datalist files in the data folder. After that, adjust the train_dataslist or the val_datalist entries in the configuration files configs/final.yaml.

3. Training and evaluation

Runing the following script to train on CASIAv2, and evalute on CASIAv1, Columbia and Coverage.

python main.py --load configs/final.yaml

For evaluating a pre-trained checkpoint:

python main.py --load configs/final.yaml --eval --resume checkpoint-path

We provide our pre-trained checkpoint here.

Citation

If you feel this project is helpful, please consider citing our paper

@inproceedings{zhai2023towards,
  title={Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning},
  author={Zhai, Yuanhao and Luan, Tianyu and Doermann, David and Yuan, Junsong},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={22390--22400},
  year={2023}
}

Acknowledgement

We would like to thank the following repos for their great work: