5 papers · 1 filter
OSCAR: Open-Set CAD Retrieval from a Language Prompt and a Single Image
Tessa Pulli, Jean-Baptiste Weibel, Peter Hönig +3
6D object pose estimation plays a crucial role in scene understanding for applications such as robotics and augmented reality. To support the needs of ever-changing object sets in…
SCOPE: Semantic Conditioning for Sim2Real Category-Level Object Pose Estimation in Robotics
Peter Hönig, Peter Hönig, Stefan Thalhammer +3
Object manipulation requires accurate object pose estimation. In open environments, robots encounter unknown objects, which requires semantic understanding in order to generalize b…
Category-Level and Open-Set Object Pose Estimation for Robotics
Peter Hönig, Matthias Hirschmanner, Markus Vincze
Object pose estimation enables a variety of tasks in computer vision and robotics, including scene understanding and robotic grasping. The complexity of a pose estimation task depe…
Enhancing Transparent Object Pose Estimation: A Fusion of GDR-Net and Edge Detection
Tessa Pulli, Peter Hönig, Stefan Thalhammer +2
Object pose estimation of transparent objects remains a challenging task in the field of robot vision due to the immense influence of lighting, background, and reflections. However…
Shape-biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation
Peter Hönig, Stefan Thalhammer, Jean-Baptiste Weibel +2
Recent advances in machine learning have greatly benefited object detection and 6D pose estimation. However, textureless and metallic objects still pose a significant challenge due…