2 citations · 4 across the 5 of their papers we have counts for
6 papers
Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving
Ahmed Abouelazm, Rupert Polley, Qingyuan Zhang +4
End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain difficult to adapt to deployment-ti…
Generative AI for Autonomous Driving: A Review
Katharina Winter, Abhishek Vivekanandan, Rupert Polley +17
Generative AI (GenAI) is rapidly advancing the field of Autonomous Driving (AD), extending beyond traditional applications in text, image, and video generation. We explore how gene…
The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Driving
Rupert Polley, Nikolai Polley, Dominik Heid +3
Traffic light perception is an essential component of the camera-based perception system for autonomous vehicles, enabling accurate detection and interpretation of traffic lights t…
Self-Supervised Pretraining for Aerial Road Extraction
Rupert Polley, Sai Vignesh Abishek Deenadayalan, J. Marius Zöllner
Deep neural networks for aerial image segmentation require large amounts of labeled data, but high-quality aerial datasets with precise annotations are scarce and costly to produce…
Empowering Autonomous Shuttles with Next-Generation Infrastructure
Sven Ochs, Melih Yazgan, Rupert Polley +9
As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how peo…
One Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th level
Sven Ochs, Jens Doll, Daniel Grimm +15
Most automated driving functions are designed for a specific task or vehicle. Most often, the underlying architecture is fixed to specific algorithms to increase performance. There…