T2IW: Joint Text to Image & Watermark Generation
An-An Liu Guokai Zhang Yuting Su Ning Xu Yongdong Zhang Lanjun Wang
Recent developments in text-conditioned image generative models have
revolutionized the production of realistic results. Unfortunately, this has
also led to an increase in privacy violations and the spread of false
information, which requires the need for traceability, privacy protection, and
other security measures. However, existing text-to-image paradigms lack the
technical capabilities to link traceable messages with image generation. In
this study, we introduce a novel task for the joint generation of text to image
and watermark (T2IW). This T2IW scheme ensures minimal damage to image quality
when generating a compound image by forcing the semantic feature and the
watermark signal to be compatible in pixels. Additionally, by utilizing
principles from Shannon information theory and non-cooperative game theory, we
are able to separate the revealed image and the revealed watermark from the
compound image. Furthermore, we strengthen the watermark robustness of our
approach by subjecting the compound image to various post-processing attacks,
with minimal pixel distortion observed in the revealed watermark. Extensive
experiments have demonstrated remarkable achievements in image quality,
watermark invisibility, and watermark robustness, supported by our proposed set
of evaluation metrics.