Search Results for author:
Found 5 papers, 2 papers with code
Synthetic Image Verification in the Era of Generative AI: What Works and What Isn't There Yet
In this work we present an overview of approaches for the detection and attribution of synthetic images and highlight their strengths and weaknesses.
Raising the Bar of AI-generated Image Detection with CLIP
The aim of this work is to explore the potential of pre-trained vision-language models (VLMs) for universal detection of AI-generated images.
M3Dsynth: A dataset of medical 3D images with AI-generated local manipulations
Here, we investigate this issue and propose M3Dsynth, a large dataset of manipulated Computed Tomography (CT) lung images.
Intriguing properties of synthetic images: from generative adversarial networks to diffusion models
Detecting fake images is becoming a major goal of computer vision.
On the detection of synthetic images generated by diffusion models
Over the past decade, there has been tremendous progress in creating synthetic media, mainly thanks to the development of powerful methods based on generative adversarial networks (GAN).
