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20182026
most citedStyle Your Face Morph and Improve Your Face Morphing Attack Detector

14 citations · 14 across the 4 of their papers we have counts for

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cs.CV2026

Non-invasive Growth Monitoring of Small Freshwater Fish in Home Aquariums via Stereo Vision

Clemens Seibold, Anna Hilsmann, Peter Eisert

Monitoring fish growth behavior provides relevant information about fish health in aquaculture and home aquariums. Yet, monitoring fish sizes poses different challenges, as fish ar…

cs.CV2026

Video-based Locomotion Analysis for Fish Health Monitoring

Timon Palm, Clemens Seibold, Anna Hilsmann +1

Monitoring the health conditions of fish is essential, as it enables the early detection of disease, safeguards animal welfare, and contributes to sustainable aquaculture practices…

cs.CV2021

Focused LRP: Explainable AI for Face Morphing Attack Detection

Clemens Seibold, Anna Hilsmann, Peter Eisert

The task of detecting morphed face images has become highly relevant in recent years to ensure the security of automatic verification systems based on facial images, e.g. automated…

cs.CV202014 cited

Style Your Face Morph and Improve Your Face Morphing Attack Detector

Clemens Seibold, Anna Hilsmann, Peter Eisert

A morphed face image is a synthetically created image that looks so similar to the faces of two subjects that both can use it for verification against a biometric verification syst…

cs.CV2018

Reflection Analysis for Face Morphing Attack Detection

Clemens Seibold, Anna Hilsmann, Peter Eisert

A facial morph is a synthetically created image of a face that looks similar to two different individuals and can even trick biometric facial recognition systems into recognizing b…

cs.CV2018

Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks

Clemens Seibold, Wojciech Samek, Anna Hilsmann +1

Artificial neural networks tend to learn only what they need for a task. A manipulation of the training data can counter this phenomenon. In this paper, we study the effect of diff…