564 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of FreiburgDE10 papers
- Georg Simon Ohm University of Applied Sciences NurembergDE5 papers
- Institut Élie Cartan de LorraineFR3 papers
- Lutheran University of Applied Sciences NurembergDE3 papers
- Université de LorraineFR3 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE2 papers
- Technical University of MunichDE2 papers
- University of KonstanzDE2 papers
- Bavarian Center for Applied Energy ResearchDE1 paper
- Bielefeld UniversityDE1 paper
- Centre for Tactile Internet with Human-in-the-LoopDE1 paper
- Columbia UniversityUS1 paper
6 papers · 1 filter
Few-Shot Panoptic Segmentation With Foundation Models
Markus Käppeler, Kürsat Petek, Niclas Vödisch +2
Current state-of-the-art methods for panoptic segmentation require an immense amount of annotated training data that is both arduous and expensive to obtain posing a significant ch…
Collaborative Dynamic 3D Scene Graphs for Automated Driving
Elias Greve, Martin Büchner, Niclas Vödisch +2
Maps have played an indispensable role in enabling safe and automated driving. Although there have been many advances on different fronts ranging from SLAM to semantics, building a…
Fast yet predictable braking manoeuvers for real-time robot control
Mazin Hamad, Jesus Gutierrez-Moreno, Hugo T. M. Kussaba +5
This paper proposes a framework for generating fast, smooth and predictable braking manoeuvers for a controlled robot. The proposed framework integrates two approaches to obtain fe…
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation
Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold +3
In policy learning for robotic manipulation, sample efficiency is of paramount importance. Thus, learning and extracting more compact representations from camera observations is a…
CoVIO: Online Continual Learning for Visual-Inertial Odometry
Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard +1
Visual odometry is a fundamental task for many applications on mobile devices and robotic platforms. Since such applications are oftentimes not limited to predefined target domains…
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation
Niclas Vödisch, Kürsat Petek, Wolfram Burgard +1
Operating a robot in the open world requires a high level of robustness with respect to previously unseen environments. Optimally, the robot is able to adapt by itself to new condi…