2 citations · 5 across the 11 of their papers we have counts for
11 papers · 1 filter
Beyond Classification: Task-Dependent Learnability under Privacy-Motivated Image Transformations
Leon Ranke, Wolfgang Hübner, Ronny Hug +2
Privacy-Enhancing Technologies (PETs) in computer vision often rely on noise or image perturbations to protect visual data while securely processing it, creating a trade-off betwee…
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…
A Causally Grounded Taxonomy for Image Degradation Robustness Evaluation
Stefan Becker, Simon Weiss, Wolfgang Hübner +1
Image degradations can occur during acquisition, processing, and transmission, altering visual appearance and affecting downstream vision tasks. They are studied in several communi…
Self-Aware Object Detection via Degradation Manifolds
Stefan Becker, Simon Weiss, Wolfgang Hübner +1
Object detectors achieve strong performance under nominal imaging conditions but can fail silently when exposed to blur, noise, compression, adverse weather, or resolution changes.…
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…
Semantic Neural Radiance Fields for Multi-Date Satellite Data
Valentin Wagner, Sebastian Bullinger, Christoph Bodensteiner +1
In this work we propose a satellite specific Neural Radiance Fields (NeRF) model capable to obtain a three-dimensional semantic representation (neural semantic field) of the scene.…
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…
Statewide Visual Geolocalization in the Wild
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
This work presents a method that is able to predict the geolocation of a street-view photo taken in the wild within a state-sized search region by matching against a database of ae…
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…
Strike the Balance: On-the-Fly Uncertainty based User Interactions for Long-Term Video Object Segmentation
Stéphane Vujasinović, Stefan Becker, Sebastian Bullinger +3
In this paper, we introduce a variant of video object segmentation (VOS) that bridges interactive and semi-automatic approaches, termed Lazy Video Object Segmentation (ziVOS). In c…
C-BEV: Contrastive Bird's Eye View Training for Cross-View Image Retrieval and 3-DoF Pose Estimation
Florian Fervers, Sebastian Bullinger, Christoph Bodensteiner +2
To find the geolocation of a street-view image, cross-view geolocalization (CVGL) methods typically perform image retrieval on a database of georeferenced aerial images and determi…