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cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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.…

cs.CV2024

YCB-LUMA: YCB Object Dataset with Luminance Keying for Object Localization

Thomas Pöllabauer

Localizing target objects in images is an important task in computer vision. Often it is the first step towards solving a variety of applications in autonomous driving, maintenance…

cs.CV2024

YCB-Ev 1.1: Event-vision dataset for 6DoF object pose estimation

Pavel Rojtberg, Thomas Pöllabauer

Our work introduces the YCB-Ev dataset, which contains synchronized RGB-D frames and event data that enables evaluating 6DoF object pose estimation algorithms using these modalitie…

cs.CV2024

FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation

Thomas Pöllabauer, Ashwin Pramod, Volker Knauthe +1

6D object pose estimation involves determining the three-dimensional translation and rotation of an object within a scene and relative to a chosen coordinate system. This problem i…