activity
20202022
most citedAnomaly Detection in Multi-Agent Trajectories for Automated Driving

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs

Osman Ülger, Julian Wiederer, Mohsen Ghafoorian +2

Graph neural networks have shown to learn effective node representations, enabling node-, link-, and graph-level inference. Conventional graph networks assume static relations betw…

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.RO20212 cited

Anomaly Detection in Multi-Agent Trajectories for Automated Driving

Julian Wiederer, Arij Bouazizi, Marco Troina +2

Human drivers can recognise fast abnormal driving situations to avoid accidents. Similar to humans, automated vehicles are supposed to perform anomaly detection. In this work, we p…

cs.CV2021

Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry

Arij Bouazizi, Julian Wiederer, Ulrich Kressel +1

We present a self-supervised learning algorithm for 3D human pose estimation of a single person based on a multiple-view camera system and 2D body pose estimates for each view. To…

cs.CV2020

Traffic Control Gesture Recognition for Autonomous Vehicles

Julian Wiederer, Arij Bouazizi, Ulrich Kressel +1

A car driver knows how to react on the gestures of the traffic officers. Clearly, this is not the case for the autonomous vehicle, unless it has road traffic control gesture recogn…