13 citations · 13 across the 7 of their papers we have counts for
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cs.CV2026
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…
cs.CV2024
Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis
Kira Maag, Roman Resner, Asja Fischer
Deep neural networks have demonstrated remarkable effectiveness across a wide range of tasks such as semantic segmentation. Nevertheless, these networks are vulnerable to adversari…
cs.CV2023★ 13 cited
Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation
Kira Maag, Asja Fischer
State-of-the-art deep neural networks have been shown to be extremely powerful in a variety of perceptual tasks like semantic segmentation. However, these networks are vulnerable t…