61 citations · 64 across the 10 of their papers we have counts for
3 papers · 1 filter
A Benchmark for Unsupervised Anomaly Detection in Multi-Agent Trajectories
Julian Wiederer, Julian Schmidt, Ulrich Kressel +2
Human intuition allows to detect abnormal driving scenarios in situations they never experienced before. Like humans detect those abnormal situations and take countermeasures to pr…
MEAT: Maneuver Extraction from Agent Trajectories
Julian Schmidt, Julian Jordan, David Raba +2
Advances in learning-based trajectory prediction are enabled by large-scale datasets. However, in-depth analysis of such datasets is limited. Moreover, the evaluation of prediction…
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention
Julian Schmidt, Julian Jordan, Franz Gritschneder +1
Predicting the motion of surrounding vehicles is essential for autonomous vehicles, as it governs their own motion plan. Current state-of-the-art vehicle prediction models heavily…