1 citations · 1 across the 5 of their papers we have counts for
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Localization in Aerial Imagery with Grid Maps using LocGAN
Haohao Hu, Junyi Zhu, Sascha Wirges +1
In this work, we present LocGAN, our localization approach based on a geo-referenced aerial imagery and LiDAR grid maps. Currently, most self-localization approaches relate the cur…
Anytime Lane-Level Intersection Estimation Based on Trajectories of Other Traffic Participants
Annika Meyer, Jonas Walter, Martin Lauer +1
Estimating and understanding the current scene is an inevitable capability of automated vehicles. Usually, maps are used as prior for interpreting sensor measurements in order to d…
An Approach to Vehicle Trajectory Prediction Using Automatically Generated Traffic Maps
Jannik Quehl, Haohao Hu, Sascha Wirges +1
Trajectory and intention prediction of traffic participants is an important task in automated driving and crucial for safe interaction with the environment. In this paper, we prese…
Momo: Monocular Motion Estimation on Manifolds
Johannes Graeter, Tobias Strauss, Martin Lauer
Knowledge about the location of a vehicle is indispensable for autonomous driving. In order to apply global localisation methods, a pose prior must be known which can be obtained f…
Pedestrian Prediction by Planning using Deep Neural Networks
Eike Rehder, Florian Wirth, Martin Lauer +1
Accurate traffic participant prediction is the prerequisite for collision avoidance of autonomous vehicles. In this work, we predict pedestrians by emulating their own motion plann…