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Found 2 papers, 1 papers with code
CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models
In this paper, we first reveal that the primary reason adversarial examples are effective as protective perturbations in latent diffusion models is the distortion of their latent representations, as demonstrated through qualitative and quantitative experiments.
Protective Perturbations against Unauthorized Data Usage in Diffusion-based Image Generation
Diffusion-based text-to-image models have shown immense potential for various image-related tasks.
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