@inproceedings{
pan2023anchmark,
title={AnchMark: Anchor-contrastive Watermarking vs Gen{AI}-based Image Modifications},
author={Minzhou Pan and Yi Zeng and Xue Lin and Ning Yu and Cho-Jui Hsieh and Ruoxi Jia},
booktitle={NeurIPS 2023 Workshop on Regulatable ML},
year={2023},
url={https://openreview.net/forum?id=WLw1oDGR2Q}
}
This work explores the evolution of watermarking techniques designed to preserve the integrity of digital image content, especially against perturbations encountered during image transmission. An overlooked vulnerability is unveiled: existing watermarks' detectability significantly drops against even moderate generative model modifications, prompting a deeper investigation into the societal implications from a policy viewpoint. In response, we propose ANCHMARK, a robust watermarking paradigm, which remarkably achieves a detection AUC exceeding 0.93 against perturbations from unseen generative models, showcasing a promising advancement in reliable watermarking amidst evolving image modification techniques.
AnchMark: Anchor-contrastive Watermarking vs GenAI-based Image Modifications
Minzhou Pan Yi Zeng Xue Lin Ning Yu Cho-Jui Hsieh Ruoxi Jia