452 citations · 783 across the 29 of their papers we have counts for
33 papers
TrackAgent: 6D Object Tracking via Reinforcement Learning
Konstantin Röhrl, Dominik Bauer, Timothy Patten +1
Tracking an object's 6D pose, while either the object itself or the observing camera is moving, is important for many robotics and augmented reality applications. While exploiting…
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…
Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects
Stefan Thalhammer, Jean-Baptiste Weibel, Markus Vincze +1
Object pose estimation is important for object manipulation and scene understanding. In order to improve the general applicability of pose estimators, recent research focuses on pr…
Open Challenges for Monocular Single-shot 6D Object Pose Estimation
Stefan Thalhammer, Peter Hönig, Jean-Baptiste Weibel +1
Object pose estimation is a non-trivial task that enables robotic manipulation, bin picking, augmented reality, and scene understanding, to name a few use cases. Monocular object p…
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…
COPE: End-to-end trainable Constant Runtime Object Pose Estimation
Stefan Thalhammer, Timothy Patten, Markus Vincze
State-of-the-art object pose estimation handles multiple instances in a test image by using multi-model formulations: detection as a first stage and then separately trained network…