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Found 5 papers, 2 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.
RMAvatar: Photorealistic Human Avatar Reconstruction from Monocular Video Based on Rectified Mesh-embedded Gaussians
We introduce RMAvatar, a novel human avatar representation with Gaussian splatting embedded on mesh to learn clothed avatar from a monocular video.
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.
Embedding Watermarks in Diffusion Process for Model Intellectual Property Protection
In practical application, the widespread deployment of diffusion models often necessitates substantial investment in training.
Intellectual Property Protection of Diffusion Models via the Watermark Diffusion Process
This paper introduces WDM, a novel watermarking solution for diffusion models without imprinting the watermark during task generation.
