MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models
Authors
Paper Information
-
Journal:
Journal of Machine Learning Research -
Added to Tracker:
Sep 09, 2026
Abstract
We introduce MarkDiffusion, an open-source Python toolkit for generative watermarking of latent diffusion models. It comprises three key components: a unified implementation framework for streamlined watermarking algorithm integration and user-friendly interfaces; a mechanism visualization suite that intuitively presents embedded and extracted watermark patterns to aid public understanding; and a comprehensive evaluation module offering standard implementations of 24 tools for assessing detectability, robustness, and output quality, plus 8 automated evaluation pipelines. Counts reflect the initial release; see the repository for the latest version. Through MarkDiffusion, we seek to assist researchers, enhance public awareness of and engagement with generative watermarking, help build consensus, and advance research and applications. Code is available at https://github.com/THU-BPM/MarkDiffusion.
Author Details
Leyi Pan
AuthorSheng Guan
AuthorZheyu Fu
AuthorLuyang Si
AuthorHuan Wang
AuthorZian Wang
AuthorHanqian Li
AuthorXuming Hu
AuthorIrwin King
AuthorPhilip S. Yu
AuthorAiwei Liu
AuthorLijie Wen
AuthorCitation Information
APA Format
Leyi Pan
,
Sheng Guan
,
Zheyu Fu
,
Luyang Si
,
Huan Wang
,
Zian Wang
,
Hanqian Li
,
Xuming Hu
,
Irwin King
,
Philip S. Yu
,
Aiwei Liu
&
Lijie Wen
.
MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models.
Journal of Machine Learning Research
.
BibTeX Format
@article{paper1658,
title = { MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models },
author = {
Leyi Pan
and Sheng Guan
and Zheyu Fu
and Luyang Si
and Huan Wang
and Zian Wang
and Hanqian Li
and Xuming Hu
and Irwin King
and Philip S. Yu
and Aiwei Liu
and Lijie Wen
},
journal = { Journal of Machine Learning Research },
url = { https://www.jmlr.org/papers/v27/25-2553.html }
}