10 citations · 19 across the 15 of their papers we have counts for
13 papers · 1 filter
Grasping the Inconspicuous
Hrishikesh Gupta, Stefan Thalhammer, Markus Leitner +1
Transparent objects are common in day-to-day life and hence find many applications that require robot grasping. Many solutions toward object grasping exist for non-transparent obje…
Event-Based high-speed low-latency fiducial marker tracking
Adam Loch, Germain Haessig, Markus Vincze
Motion and dynamic environments, especially under challenging lighting conditions, are still an open issue for robust robotic applications. In this paper, we propose an end-to-end…
UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments
Pablo Martinez-Gonzalez, Sergiu Oprea, John Alejandro Castro-Vargas +4
Synthetic data generation has become essential in last years for feeding data-driven algorithms, which surpassed traditional techniques performance in almost every computer vision…
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…