Your Text Encoder Can Be An Object-Level Watermarking Controller
Journal:
arXiv
Published Date:
Mar 15, 2025
Abstract
Invisible watermarking of AI-generated images can help with copyright
protection, enabling detection and identification of AI-generated media. In
this work, we present a novel approach to watermark images of T2I Latent
Diffusion Models (LDMs). By only fine-tuning text token embeddings $W_*$, we
enable watermarking in selected objects or parts of the image, offering greater
flexibility compared to traditional full-image watermarking. Our method
leverages the text encoder's compatibility across various LDMs, allowing
plug-and-play integration for different LDMs. Moreover, introducing the
watermark early in the encoding stage improves robustness to adversarial
perturbations in later stages of the pipeline. Our approach achieves $99\%$ bit
accuracy ($48$ bits) with a $10^5 \times$ reduction in model parameters,
enabling efficient watermarking.
