5 papers
Attention-based Vehicle Self-Localization with HD Feature Maps
Nico Engel, Vasileios Belagiannis, Klaus Dietmayer
We present a vehicle self-localization method using point-based deep neural networks. Our approach processes measurements and point features, i.e. landmarks, from a high-definition…
Point Transformer
Nico Engel, Vasileios Belagiannis, Klaus Dietmayer
In this work, we present Point Transformer, a deep neural network that operates directly on unordered and unstructured point sets. We design Point Transformer to extract local and…
DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration
Markus Horn, Nico Engel, Vasileios Belagiannis +2
This work addresses the problem of point cloud registration using deep neural networks. We propose an approach to predict the alignment between two point clouds with overlapping da…
DeepLocalization: Landmark-based Self-Localization with Deep Neural Networks
Nico Engel, Stefan Hoermann, Markus Horn +2
We address the problem of vehicle self-localization from multi-modal sensor information and a reference map. The map is generated off-line by extracting landmarks from the vehicle'…
Deep Object Tracking on Dynamic Occupancy Grid Maps Using RNNs
Nico Engel, Stefan Hoermann, Philipp Henzler +1
The comprehensive representation and understanding of the driving environment is crucial to improve the safety and reliability of autonomous vehicles. In this paper, we present a n…