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FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models
May 7, 2024, 4:48 a.m. | Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang
cs.CV updates on arXiv.org arxiv.org
Abstract: Text-to-image generative models, especially those based on latent diffusion models (LDMs), have demonstrated outstanding ability in generating high-quality and high-resolution images from textual prompts. With this advancement, various fine-tuning methods have been developed to personalize text-to-image models for specific applications such as artistic style adaptation and human face transfer. However, such advancements have raised copyright concerns, especially when the data are used for personalization without authorization. For example, a malicious user can employ fine-tuning techniques …
abstract advancement applications arxiv cs.cr cs.cv diffusion diffusion models fine-tuning generative generative models image image diffusion images latent diffusion models prompts quality resolution style text text-to-image textual type watermark
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