6 papers
Semantic Segmentation of Transparent and Opaque Drinking Glasses with the Help of Zero-shot Learning
Annalena Blänsdorf, Tristan Wirth, Arne Rak +3
Segmenting transparent structures in images is challenging since they are difficult to distinguish from the background. Common examples are drinking glasses, which are a ubiquitous…
Improving 6D Object Pose Estimation of metallic Household and Industry Objects
Thomas Pöllabauer, Michael Gasser, Tristan Wirth +3
6D object pose estimation suffers from reduced accuracy when applied to metallic objects. We set out to improve the state-of-the-art by addressing challenges such as reflections an…
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation
Zixuan Fang, Thomas Pöllabauer, Tristan Wirth +3
In industrial applications requiring real-time feedback, such as quality control and robotic manipulation, the demand for high-speed and accurate pose estimation remains critical.…
Transparency Distortion Robustness for SOTA Image Segmentation Tasks
Volker Knauthe, Arne Rak, Tristan Wirth +4
Semantic Image Segmentation facilitates a multitude of real-world applications ranging from autonomous driving over industrial process supervision to vision aids for human beings.…
Influence of Water Droplet Contamination for Transparency Segmentation
Volker Knauthe, Paul Weitz, Thomas Pöllabauer +4
Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. W…
An Empirical Study of Uncertainty Estimation Techniques for Detecting Drift in Data Streams
Anton Winter, Nicolas Jourdan, Tristan Wirth +2
In safety-critical domains such as autonomous driving and medical diagnosis, the reliability of machine learning models is crucial. One significant challenge to reliability is conc…