Karsten Haug — accepted AI-conference papers

2024

Enhancing Online Road Network Perception and Reasoning with Standard Definition Maps

Hengyuan Zhang, David Paz, Yuliang Guo, Arun Das, Xinyu Huang, Karsten Haug +2

IROS 2024poster

Autonomous driving for urban and highway driving applications often requires High Definition (HD) maps to generate a navigation plan. Nevertheless, various challenges arise when generating and maintaining HD maps at scale. While recent online mapping methods have started to emerge, their performance…

Cited by 5 Source ↗code ↗Scholar ↗

2024

Self-Supervised Representation Learning From Temporal Ordering of Automated Driving Sequences

Christopher Lang, Alexander Braun, Lars Schillingmann, Karsten Haug, Abhinav Valada

RA-L 2024

Self-supervised feature learning enables perception systems to benefit from the vast raw data recorded by vehicle fleets worldwide. While video-level self-supervised approaches have shown strong generalizability on classification tasks, the potential to learn dense representations from sequential da

Cited by 14 Source ↗Scholar ↗