2 citations · 2 across the 9 of their papers we have counts for
11 papers
GroupEnsemble: Efficient Uncertainty Estimation for DETR-based Object Detection
Yutong Yang, Katarina Popović, Julian Wiederer +3
Detection Transformer (DETR) and its variants show strong performance on object detection, a key task for autonomous systems. However, a critical limitation of these models is that…
LSA: Localized Semantic Alignment for Enhancing Temporal Consistency in Traffic Video Generation
Mirlan Karimov, Teodora Spasojevic, Markus Braun +3
Controllable video generation has emerged as a versatile tool for autonomous driving, enabling realistic synthesis of traffic scenarios. However, existing methods depend on control…
Initial Baryon Stopping and Angular Momentum in Heavy-Ion Collisions
Alex Akridge, Daniel Gallimore, Hector Morales +1
Noncentral heavy-ion collisions create fireballs with large initial orbital angular momentum that is expected to induce strong vorticity in the hot bulk fluid and generate global s…
SVS-GAN: Leveraging GANs for Semantic Video Synthesis
Khaled M. Seyam, Julian Wiederer, Markus Braun +1
In recent years, there has been a growing interest in Semantic Image Synthesis (SIS) through the use of Generative Adversarial Networks (GANs) and diffusion models. This field has…
Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction
Julian Wiederer, Julian Schmidt, Ulrich Kressel +2
Despite the significant research efforts on trajectory prediction for automated driving, limited work exists on assessing the prediction reliability. To address this limitation we…
RESET: Revisiting Trajectory Sets for Conditional Behavior Prediction
Julian Schmidt, Pascal Huissel, Julian Wiederer +3
It is desirable to predict the behavior of traffic participants conditioned on different planned trajectories of the autonomous vehicle. This allows the downstream planner to estim…
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…
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…
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…
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…
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…