Localised Frequency Latent Domain Watermarking of DDIM Generated Images

Stable Diffusion models, relying on iterative generative latent diffusion processes, have recently achieved remarkable results in producing realistic and diverse images. Meanwhile, the widespread application of generative models raised significant concerns about the origins of image content or the infringement of intellectual property rights. Consequently, a method for identifying AI generated images and/or other information about their origins is imperatively necessary. To address these requirements we propose to embed watermarks during one of the diffusion iterative steps of the DDIM. Such watermarks are required to be recoverable while also robust to possible changes to the generated watermarked images. The watermarks are embedded in the localized regions of the latent space frequencies. The binary watermarks are detected from the generated watermarked images by means of a CNN watermark detector. The robustness of the CNN watermark detector is improved through training by considering various distortions to the watermarked images.