46 citations · 70 across the 5 of their papers we have counts for
6 papers
ALOOD: Exploiting Language Representations for LiDAR-based Out-of-Distribution Object Detection
Michael Kösel, Marcel Schreiber, Michael Ulrich +2
LiDAR-based 3D object detection plays a critical role for reliable and safe autonomous driving systems. However, existing detectors often produce overly confident predictions for o…
Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection
Michael Kösel, Marcel Schreiber, Michael Ulrich +2
LiDAR-based 3D object detection has become an essential part of automated driving due to its ability to localize and classify objects precisely in 3D. However, object detectors fac…
A Multi-Task Recurrent Neural Network for End-to-End Dynamic Occupancy Grid Mapping
Marcel Schreiber, Vasileios Belagiannis, Claudius Gläser +1
A common approach for modeling the environment of an autonomous vehicle are dynamic occupancy grid maps, in which the surrounding is divided into cells, each containing the occupan…
Dynamic Occupancy Grid Mapping with Recurrent Neural Networks
Marcel Schreiber, Vasileios Belagiannis, Claudius Gläser +1
Modeling and understanding the environment is an essential task for autonomous driving. In addition to the detection of objects, in complex traffic scenarios the motion of other ro…
Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks
Marcel Schreiber, Vasileios Belagiannis, Claudius Glaeser +1
In this work, we tackle the problem of modeling the vehicle environment as dynamic occupancy grid map in complex urban scenarios using recurrent neural networks. Dynamic occupancy…
Long-Term Occupancy Grid Prediction Using Recurrent Neural Networks
Marcel Schreiber, Stefan Hoermann, Klaus Dietmayer
We tackle the long-term prediction of scene evolution in a complex downtown scenario for automated driving based on Lidar grid fusion and recurrent neural networks (RNNs). A bird's…