6 papers
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…
Phys-Liquid: A Physics-Informed Dataset for Estimating 3D Geometry and Volume of Transparent Deformable Liquids
Ke Ma, Yizhou Fang, Jean-Baptiste Weibel +5
Estimating the geometric and volumetric properties of transparent deformable liquids is challenging due to optical complexities and dynamic surface deformations induced by containe…
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…
ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning
Hrishikesh Gupta, Stefan Thalhammer, Jean-Baptiste Weibel +2
Transparent objects are ubiquitous in daily life, making their perception and robotics manipulation important. However, they present a major challenge due to their distinct refract…
Challenges for Monocular 6D Object Pose Estimation in Robotics
Stefan Thalhammer, Dominik Bauer, Peter Hönig +3
Object pose estimation is a core perception task that enables, for example, object grasping and scene understanding. The widely available, inexpensive and high-resolution RGB senso…
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…