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Structured Adversarial Camouflage via Voronoi Diagrams
Jens Bayer, Stefan Becker, David Münch +2
Pixel-wise adversarial patches are computationally heavy and often visually detectable, limiting utility in security-critical systems. We present adversarial Voronoi camouflage tha…
Higher-Order Adversarial Patches for Real-Time Object Detectors
Jens Bayer, Stefan Becker, David Münch +2
Higher-order adversarial attacks can directly be considered the result of a cat-and-mouse game -- an elaborate action involving constant pursuit, near captures, and repeated escape…
Traversing the Subspace of Adversarial Patches
Jens Bayer, Stefan Becker, David Münch +2
Despite ongoing research on the topic of adversarial examples in deep learning for computer vision, some fundamentals of the nature of these attacks remain unclear. As the manifold…
Network transferability of adversarial patches in real-time object detection
Jens Bayer, Stefan Becker, David Münch +1
Adversarial patches in computer vision can be used, to fool deep neural networks and manipulate their decision-making process. One of the most prominent examples of adversarial pat…
Utilizing dataset affinity prediction in object detection to assess training data
Stefan Becker, Jens Bayer, Ronny Hug +2
Data pooling offers various advantages, such as increasing the sample size, improving generalization, reducing sampling bias, and addressing data sparsity and quality, but it is no…
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection
Jens Bayer, David Münch, Michael Arens
Deep neural networks, especially convolutional deep neural networks, are state-of-the-art methods to classify, segment or even generate images, movies, or sounds. However, these me…