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Adversarial Robustness of AI-Generated Image Detectors in the Real World
Sina Mavali, Jonas Ricker, David Pape +2
The rapid advancement of Generative Artificial Intelligence (GenAI) capabilities is accompanied by a concerning rise in its misuse. In particular the generation of credible misinfo…
BIAS-ID: A Framework for Analyzing Transformation Biases in AI-Generated Image Detectors
Jonas Ricker, Asja Fischer, Erwin Quiring
Given the surge of harmful AI-generated imagery online, reliably distinguishing authentic images from generated ones has become an urgent research topic. While many proposed detect…
PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images
Simon Damm, Jonas Ricker, Henning Petzka +1
Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large language models, they allow for e…
SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation
Christian Gehrmann, Jonas Ricker, Simon Damm +5
In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptographic applications and high-stakes scen…
"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation
Sandra Höltervennhoff, Jonas Ricker, Maike M. Raphael +6
As generative AI is increasingly contributing to the spread of deceptively realistic misinformation, lawmakers have introduced regulations requiring the disclosure of AI-generated…