Quentin Bammey

Diffusion models excel at generating photorealistic images, yet their outputs betray a hidden signature: spectral artefacts — distinct anormalies in the frequency domain that deviate from natural image statistics. This webinar will unpack the mathematical underpinnings behind these artefacts, revealing why and how incorrect frequencies emerge during the generation process. We will discuss the extent to which frequency artefacts can be exploited as reliable markers to identify deepfakes, offering new tools for image forensics. Finally, we will explore strategies to mitigate these errors, paving the way for more accurate and robust image synthesis. Join us for an in-depth exploration at the intersection of signal processing and generative AI!