most citedOne Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th level

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20251 cited

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…

cs.CV20251 cited

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…

cs.CV2025

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…

cs.RO2024

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…

cs.RO20242 cited

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…