6 citations · 7 across the 4 of their papers we have counts for
5 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…
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…
Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme
Jean-Baptiste Weibel, Timothy Patten, Markus Vincze
While object semantic understanding is essential for most service robotic tasks, 3D object classification is still an open problem. Learning from artificial 3D models alleviates th…
Addressing the Sim2Real Gap in Robotic 3D Object Classification
Jean-Baptiste Weibel, Timothy Patten, Markus Vincze
Object classification with 3D data is an essential component of any scene understanding method. It has gained significant interest in a variety of communities, most notably in robo…