5 papers
Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence
Robert Aufschläger, Youssef Shoeb, Azarm Nowzad +3
The collection and release of street-level recordings as Open Data play a vital role in advancing autonomous driving systems and AI research. However, these datasets pose significa…
Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art
Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk
In this paper, we review the state of the art in Out-of-Distribution (OoD) segmentation, with a focus on road obstacle detection in automated driving as a real-world application. W…
Adaptive Neural Networks for Intelligent Data-Driven Development
Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk
Advances in machine learning methods for computer vision tasks have led to their consideration for safety-critical applications like autonomous driving. However, effectively integr…
Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios
Youssef Shoeb, Nazir Nayal, Azarm Nowzad +2
Detecting road obstacles is essential for autonomous vehicles to navigate dynamic and complex traffic environments safely. Current road obstacle detection methods typically assign…
A Likelihood Ratio-Based Approach to Segmenting Unknown Objects
Nazir Nayal, Youssef Shoeb, Fatma Güney
Addressing the Out-of-Distribution (OoD) segmentation task is a prerequisite for perception systems operating in an open-world environment. Large foundational models are frequently…