activity
20182025
most citedTeam NimbRo at MBZIRC 2017: Fast Landing on a Moving Target and Treasure Hunting with a Team of MAVs

35 citations · 79 across the 10 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.CV2019

LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

Radu Alexandru Rosu, Peer Schütt, Jan Quenzel +1

Deep convolutional neural networks (CNNs) have shown outstanding performance in the task of semantically segmenting images. However, applying the same methods on 3D data still pose…

cs.CV201914 cited

Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes

Radu Alexandru Rosu, Jan Quenzel, Sven Behnke

Scene understanding is an important capability for robots acting in unstructured environments. While most SLAM approaches provide a geometrical representation of the scene, a seman…

cs.CV2019

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

Jens Behley, Martin Garbade, Andres Milioto +4

Semantic scene understanding is important for various applications. In particular, self-driving cars need a fine-grained understanding of the surfaces and objects in their vicinity…

cs.RO2019

Detection and Tracking of Small Objects in Sparse 3D Laser Range Data

Jan Razlaw, Jan Quenzel, Sven Behnke

Detection and tracking of dynamic objects is a key feature for autonomous behavior in a continuously changing environment. With the increasing popularity and capability of micro ae…

cs.RO201935 cited

Team NimbRo at MBZIRC 2017: Fast Landing on a Moving Target and Treasure Hunting with a Team of MAVs

Marius Beul, Matthias Nieuwenhuisen, Jan Quenzel +5

The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 has defined ambitious new benchmarks to advance the state-of-the-art in autonomous operation of ground-based an…