Recently developed text-to-image diffusion models make it easy to edit or create high-quality images. Their ease of use has raised concerns about the potential for malicious editing or deepfake creation. Imperceptible perturbations have been proposed as a means of protecting images from malicious editing by preventing diffusion models from generating realistic images. However, we find that the aforementioned perturbations are not robust to JPEG compression, which poses a major weakness because of the common usage and availability of JPEG. We discuss the importance of robustness for additive imperceptible perturbations and encourage alternative approaches to protect images against editing.
翻译:最近开发的文本转图像扩散模型使得编辑或创建高质量图像变得更加容易。其易用性引起了对恶意编辑或深度伪造创建的担忧。提出了微不可见的扰动作为一种保护图像免受恶意编辑的手段,通过防止扩散模型生成逼真图像来实现。然而,我们发现上述扰动对JPEG压缩不具备鲁棒性,这是一种主要的弱点,因为JPEG的常见用途和可用性。我们讨论了鲁棒性对于加性微不可见扰动的重要性,并鼓励采用替代方法来保护图像免受编辑。