T2IW: Joint Text to Image & Watermark Generation

TL;DR

This paper introduces T2IW, a joint text-to-image and watermark generation method that enhances image traceability and privacy by embedding robust, minimally invasive watermarks during image creation, supported by theoretical and experimental validation.

Contribution

It proposes a novel joint text-to-image and watermark generation framework that maintains image quality and watermark robustness, utilizing Shannon information theory and game theory for separation.

Findings

High-quality image generation with minimal watermark distortion

Enhanced watermark robustness against post-processing attacks

Effective separation of image and watermark signals

Abstract

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.