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:最近开发的文本到图像扩散模型使得编辑或创建高质量图像变得容易。它们的易用性引起了对恶意编辑或深度伪造创建的担忧。被提出的不可察觉扰动被视为一种防止扩散模型生成真实图像的手段,从而保护图像免受恶意编辑的影响。然而,我们发现上述扰动不具备对JPEG压缩的鲁棒性,这是一种重大弱点,因为JPEG的使用和可用性很常见。我们讨论了对加性不可察觉扰动的鲁棒性的重要性,并鼓励采用其他方法来保护图像免受编辑的影响。