MaXsive embeds a continuous Gaussian watermark into the initial latent noise of a diffusion model and injects an independent X-shaped Fourier template so rotated, scaled, and translated images can be corrected before watermark extraction.
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MaXsive: High-Capacity and Robust Training-Free Generative Image Watermarking in Diffusion Models
MaXsive embeds a continuous Gaussian watermark into the initial latent noise of a diffusion model and injects an independent X-shaped Fourier template so rotated, scaled, and translated images can be corrected before watermark extraction.