Daniel Stadler

An Approach to Systematic Data Acquisition and Data-Driven Simulation for the Safety Testing of Automated Driving Functions

With growing complexity and criticality of automated driving functions in road traffic and their operational design domains (ODD), there is increasing demand for covering significant proportions...

A Joint Approach Towards Data-Driven Virtual Testing for Automated Driving: The AVEAS Project

With growing complexity and responsibility of automated driving functions in road traffic and growing scope of their operational design domains, there is increasing demand for covering significant...

Improving Multiple Pedestrian Tracking by Track Management and Occlusion Handling

An Improved Association Pipeline for Multi-Person Tracking

An Occlusion-Aware Multi-Target Multi-Camera Tracking System

A Strong Baseline for Multi-Person Tracking in Thermal Infrared Imagery

Multi-Pedestrian Tracking with Clusters

Utilizing Category-Specific Re-Identification Models in Drone-Based Multi-Class Multi-Object Tracking

On the Performance of Crowd-Specific Detectors in Multi-Pedestrian Tracking

BYTEv2: Associating More Detection Boxes Under Occlusion for Improved Multi-person Tracking

Past Information Aggregation for Multi-Person Tracking

VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results

VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results

PAS Tracker: Position-, Appearance- and Size-Aware Multi-object Tracking in Drone Videos

Modelling Ambiguous Assignments for Multi-Person Tracking in Crowds

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Advancing Robust Infrared Object Detection: Practical Insights on Model Development and Evaluation

From Real-World Traffic Data to Relevant Critical Scenarios

The reliable operation of autonomous vehicles, automated driving functions, and advanced driver assistance systems across a wide range of relevant scenarios is critical for their development and...