Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality

Understand

Diffusion models recently have been successfully applied for the visual synthesis of strikingly realistic appearing images.

• This raises strong concerns about their potential for malicious purposes.
• In this paper, we propose using the lightweight multi Local Intrinsic Dimensionality (multiLID), which has been originally developed in context of the detection of adversarial examples, for the automatic detection of synthetic images and the identification of the according generator networks.
• In contrast to many existing detection approaches, which often only work for GAN-generated images, the proposed method provides close to perfect detection results in many realistic use cases.