1 citations · 1 across the 4 of their papers we have counts for
5 papers
UGainS: Uncertainty Guided Anomaly Instance Segmentation
Alexey Nekrasov, Alexander Hermans, Lars Kuhnert +1
A single unexpected object on the road can cause an accident or may lead to injuries. To prevent this, we need a reliable mechanism for finding anomalous objects on the road. This…
Multi-Camera Visual-Inertial Simultaneous Localization and Mapping for Autonomous Valet Parking
Marcus Abate, Ariel Schwartz, Xue Iuan Wong +6
Localization and mapping are key capabilities for self-driving vehicles. In this paper, we build on Kimera and extend it to use multiple cameras as well as external (eg wheel) odom…
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping
Daniel Bauer, Lars Kuhnert, Lutz Eckstein
With the recent boost in autonomous driving, increased attention has been paid on radars as an input for occupancy mapping. Besides their many benefits, the inference of occupied s…
Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework
Daniel Bauer, Lars Kuhnert, Lutz Eckstein
To perform high speed tasks, sensors of autonomous cars have to provide as much information in as few time steps as possible. However, radars, one of the sensor modalities autonomo…
Deep, spatially coherent Occupancy Maps based on Radar Measurements
Daniel Bauer, Lars Kuhnert, Lutz Eckstein
One essential step to realize modern driver assistance technology is the accurate knowledge about the location of static objects in the environment. In this work, we use artificial…