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Found 5 papers, 3 papers with code
AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images
Recent advances in the field of generative artificial intelligence (AI) have blurred the lines between authentic and machine-generated content, making it almost impossible for humans to distinguish between such media.
AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error
A key enabler for generating high-resolution images with low computational cost has been the development of latent diffusion models (LDMs).
A Representative Study on Human Detection of Artificially Generated Media Across Countries
To further understand which factors influence people's ability to detect generated media, we include personal variables, chosen based on a literature review in the domains of deepfake and fake news research.
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Recent breakthroughs in generative modeling have sparked interest in practical single-model attribution.
Towards the Detection of Diffusion Model Deepfakes
However, relatively little attention has been paid to the detection of DM-generated images, which is critical to prevent adverse impacts on our society.
