MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models

• URL: http://arxiv.org/abs/2509.10569v2
• Date: Thu, 16 Oct 2025 07:42:56 GMT
• Title: MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models
• Authors: 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,
• Abstract summary: MarkDiffusion is an open-source Python toolkit for generative watermarking of latent diffusion models.<n>It comprises three key components: a unified implementation framework for streamlined watermarking algorithm integrations; a mechanism visualization suite that intuitively showcases added and extracted watermark patterns to aid public understanding; and a comprehensive evaluation module offering standard implementations of 24 tools across three essential aspects - detectability, robustness, and output quality - plus 8 automated evaluation pipelines.
• Score: 100.18689534574376
• License: http://creativecommons.org/licenses/by/4.0/
• 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 integrations and user-friendly interfaces; a mechanism visualization suite that intuitively showcases added and extracted watermark patterns to aid public understanding; and a comprehensive evaluation module offering standard implementations of 24 tools across three essential aspects - detectability, robustness, and output quality - plus 8 automated evaluation pipelines. Through MarkDiffusion, we seek to assist researchers, enhance public awareness and engagement in generative watermarking, and promote consensus while advancing research and applications.

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