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Generative Watermarking Against Unauthorized Subject-Driven Image Synthesis. (arXiv:2306.07754v1 [cs.CV])
cs.CR updates on arXiv.org arxiv.org
Large text-to-image models have shown remarkable performance in synthesizing
high-quality images. In particular, the subject-driven model makes it possible
to personalize the image synthesis for a specific subject, e.g., a human face
or an artistic style, by fine-tuning the generic text-to-image model with a few
images from that subject. Nevertheless, misuse of subject-driven image
synthesis may violate the authority of subject owners. For example, malicious
users may use subject-driven synthesis to mimic specific artistic styles or to
create fake facial …
generative high human images large performance quality text watermarking