Detecting Images Generated by Diffusers

by   Davide Alessandro Coccomini, et al.
Consiglio Nazionale delle Ricerche

This paper explores the task of detecting images generated by text-to-image diffusion models. To evaluate this, we consider images generated from captions in the MSCOCO and Wikimedia datasets using two state-of-the-art models: Stable Diffusion and GLIDE. Our experiments show that it is possible to detect the generated images using simple Multi-Layer Perceptrons (MLPs), starting from features extracted by CLIP, or traditional Convolutional Neural Networks (CNNs). We also observe that models trained on images generated by Stable Diffusion can detect images generated by GLIDE relatively well, however, the reverse is not true. Lastly, we find that incorporating the associated textual information with the images rarely leads to significant improvement in detection results but that the type of subject depicted in the image can have a significant impact on performance. This work provides insights into the feasibility of detecting generated images, and has implications for security and privacy concerns in real-world applications.


DIRE for Diffusion-Generated Image Detection

Diffusion models have shown remarkable success in visual synthesis, but ...

Inspecting the Geographical Representativeness of Images from Text-to-Image Models

Recent progress in generative models has resulted in models that produce...

Exposing the Fake: Effective Diffusion-Generated Images Detection

Image synthesis has seen significant advancements with the advent of dif...

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models

Recently, Generative Diffusion Models (GDMs) have showcased their remark...

On the De-duplication of LAION-2B

Generative models, such as DALL-E, Midjourney, and Stable Diffusion, hav...

Towards the Detection of Diffusion Model Deepfakes

Diffusion models (DMs) have recently emerged as a promising method in im...

The Stable Signature: Rooting Watermarks in Latent Diffusion Models

Generative image modeling enables a wide range of applications but raise...

Please sign up or login with your details

Forgot password? Click here to reset