17 citations · 17 across the 3 of their papers we have counts for
4 papers · 1 filter
Bosch Street Dataset: A Multi-Modal Dataset with Imaging Radar for Automated Driving
Karim Armanious, Maurice Quach, Michael Ulrich +25
This paper introduces the Bosch street dataset (BSD), a novel multi-modal large-scale dataset aimed at promoting highly automated driving (HAD) and advanced driver-assistance syste…
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…
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars
Florian Drews, Di Feng, Florian Faion +3
We propose DeepFusion, a modular multi-modal architecture to fuse lidars, cameras and radars in different combinations for 3D object detection. Specialized feature extractors take…
Self-Supervised Velocity Estimation for Automotive Radar Object Detection Networks
Daniel Niederlöhner, Michael Ulrich, Sascha Braun +5
This paper presents a method to learn the Cartesian velocity of objects using an object detection network on automotive radar data. The proposed method is self-supervised in terms…