most citedCRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.RO2022

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…

cs.CV2022★ 1 cited

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…