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Worst-Case Morphs: a Theoretical and a Practical Approach
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Datum
2022
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Gesellschaft für Informatik e.V.
Zusammenfassung
Face Recognition (FR) systems have been shown to be vulnerable to morphing attacks.
We examine exactly how challenging morphs can become. By showing a worst-case construction in
the embedding space of an FR system and using a mapping from embedding space back to image
space we generate images that show that this theoretical upper bound can be approximated if the FR
system is known. The resulting morphs can also succesfully fool unseen FR systems and are useful
for exploring and understanding the weaknesses of FR systems. Our method contributes to gaining
more insight into the vulnerability of FR systems.