RingID 🔍

RingID: Rethinking Tree-Ring Watermarking for Enhanced Multi-Key Identification

[Hai Ci](https://scholar.google.com/citations?user=GMrjppAAAAAJ&hl=en)^* Pei Yang^* [Yiren Song](https://scholar.google.com/citations?user=L2YS0jgAAAAJ&hl=en&oi=ao)^* [Mike Zheng Shou](https://sites.google.com/view/showlab) National University of Singapore [Project Page](https://sites.google.com/view/ringid2?usp=sharing) | [Arxiv](http://arxiv.org/abs/2404.14055)

RingID presents a robust diffusion image watermarking approach to imprint multiple keys. It bases on the training-free approach Tree-Ring_[1], but significantly enhances in both watermark verification and multi-key identification.

Method

RingID identifies the limitations in Tree-Ring's design and suggests a series of approaches for enhanced distinguishability and robustness.

Dependencies

PyTorch == 1.13.0
transformers == 4.23.1
diffusers == 0.11.1
datasets

Note: higher diffusers version may not be compatible with the DDIM inversion code.

Usage

Verification

python verify.py --run_name verification --online

Identification

python identify.py --run_name identification --online

Citation

@article{ci2024ringid,
  title={RingID: Rethinking Tree-Ring Watermarking for Enhanced Multi-Key Identification},
  author={Ci, Hai and Yang, Pei and Song, Yiren and Shou, Mike Zheng},
  journal={arXiv preprint arXiv:2404.14055},
  year={2024}
}

Acknowledgement

[1] Tree-ring watermarks: Fingerprints for diffusion images that are invisible and robust

showlab / RingID

readme