1 citations · 1 across the 6 of their papers we have counts for
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ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
Dominik Bauer, Timothy Patten, Markus Vincze
Point cloud registration is a common step in many 3D computer vision tasks such as object pose estimation, where a 3D model is aligned to an observation. Classical registration met…
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…
PyraPose: Feature Pyramids for Fast and Accurate Object Pose Estimation under Domain Shift
Stefan Thalhammer, Markus Leitner, Timothy Patten +1
Object pose estimation enables robots to understand and interact with their environments. Training with synthetic data is necessary in order to adapt to novel situations. Unfortuna…
Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images
Kiru Park, Timothy Patten, Markus Vincze
Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses. However, it is difficult to obtain tex…
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…
VeREFINE: Integrating Object Pose Verification with Physics-guided Iterative Refinement
Dominik Bauer, Timothy Patten, Markus Vincze
Accurate and robust object pose estimation for robotics applications requires verification and refinement steps. In this work, we propose to integrate hypotheses verification with…