设计了不同的算法来生成对抗性噪声,以自适应基于扩散过程和微调过程的DreamBooth过程; 在两个人脸基准测试中广泛评估了所提出的方法,并在不同的配置下有效地工作。 一句话总结: 提出一种名为Anti-DreamBooth的防御系统,旨在通过为用户的图像添加微妙的噪声干扰,来防止恶意使用DreamBooth生成虚假的图像。 Text-to-imag...
More impressively, Anti-DreamBooth maintains its efficiency even under adverse conditions, such as model or prompt/term mismatching between training and testing. In summary, our contributions include: (1) We discuss the potential negative impact of personalized te...
提出一种名为Anti-DreamBooth的防御系统,旨在通过为用户的图像添加微妙的噪声干扰,来防止恶意使用DreamBooth生成虚假的图像。【转发】@爱可可-爱生活:[CV]《Anti-DreamBooth: Protecting users from personali...
In this paper, we explore a defense system called Anti-DreamBooth against such malicious use of DreamBooth. The system aims to add subtle noise perturbation to each user's image before publishing in order to disrupt the generation quality of any DreamBooth model trained on these perturbed ...