PiGW: A Plug-in Generative Watermarking Framework
arxiv(2024)
摘要
Integrating watermarks into generative images is a critical strategy for
protecting intellectual property and enhancing artificial intelligence
security. This paper proposes Plug-in Generative Watermarking (PiGW) as a
general framework for integrating watermarks into generative images. More
specifically, PiGW embeds watermark information into the initial noise using a
learnable watermark embedding network and an adaptive frequency spectrum mask.
Furthermore, it optimizes training costs by gradually increasing timesteps.
Extensive experiments demonstrate that PiGW enables embedding watermarks into
the generated image with negligible quality loss while achieving true
invisibility and high resistance to noise attacks. Moreover, PiGW can serve as
a plugin for various commonly used generative structures and multimodal
generative content types. Finally, we demonstrate how PiGW can also be utilized
for detecting generated images, contributing to the promotion of secure AI
development. The project code will be made available on GitHub.
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