4 papers
SearchAD: Large-Scale Rare Image Retrieval Dataset for Autonomous Driving
Felix Embacher, Jonas Uhrig, Marius Cordts +1
Retrieving rare and safety-critical driving scenarios from large-scale datasets is essential for building robust autonomous driving (AD) systems. As dataset sizes continue to grow,…
What Matters for Scalable and Robust Learning in End-to-End Driving Planners?
David Holtz, Niklas Hanselmann, Simon Doll +2
End-to-end autonomous driving has gained significant attention for its potential to learn robust behavior in interactive scenarios and scale with data. Popular architectures often…
AGO: Adaptive Grounding for Open World 3D Occupancy Prediction
Peizheng Li, Shuxiao Ding, You Zhou +6
Open-world 3D semantic occupancy prediction aims to generate a voxelized 3D representation from sensor inputs while recognizing both known and unknown objects. Transferring open-vo…
EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners
Niklas Hanselmann, Simon Doll, Marius Cordts +2
To handle the complexities of real-world traffic, learning planners for self-driving from data is a promising direction. While recent approaches have shown great progress, they typ…