This repository is the source code for "How to Trace Latent Generative Model Generated Images without Artificial Watermark?" (ICML 2024).
see requirements.txt
For example, generating images using Stable Diffusion v1-5:
python generate_samples_all.py --arch sd --save_dir ./sdv15_generated_imgs/Generating images using Stable Diffusion v2-base:
python generate_samples_all.py --arch sdv2base --save_dir ./sdv2base_generated_imgs/For example, to conduct reverse-engineering on the belonging images of Stable Diffusion Stable Diffusion v2-base:
python run_write_re_loss_to_txt.py --gpu 4 --filePath ./sdv2base_generated_imgs/ --model_type sdv2base --lr 0.05 \
--num_iter 100 --write_txt_path ./ReconstructionLosses_Model_sdv2base_Images_sdv2baseGenerated.txtTo conduct reverse-engineering on the non-belonging images (images generated by Stable Diffusion v1-5 here):
python run_write_re_loss_to_txt.py --gpu 4 --filePath ./sdv15_generated_imgs/ --model_type sdv2base --lr 0.05 \
--num_iter 100 --write_txt_path ./ReconstructionLosses_Model_sdv2base_Images_sdv15Generated.txtpython detection.py \
--txt_1 ./ReconstructionLosses_Model_sdv2base_Images_sdv2baseGenerated.txt \
--txt_2 ./ReconstructionLosses_Model_sdv2base_Images_sdv15Generated.txt \
--label_1 'Belongings' \
--label_2 'Non-belongings' \
--save_name ./distribution.pdfYou are encouraged to cite the following papers if you use the repo for academic research.
@inproceedings{wang2024trace,
title={How to Trace Latent Generative Model Generated Images without Artificial Watermark?},
author={Wang, Zhenting and Sehwag Vikash, Chen, Chen and Lyu, Lingjuan and Metaxas, Dimitris N and Ma, Shiqing},
booktitle={International Conference on Machine Learning},
year={2024}
}
@inproceedings{wang2023did,
title={Where Did I Come From? Origin Attribution of AI-Generated Images},
author={Wang, Zhenting and Chen, Chen and Zeng, Yi and Lyu, Lingjuan and Ma, Shiqing},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023}
}