28 citations · 136 across the 33 of their papers we have counts for
5 papers · 1 filter
DriveLM: Driving with Graph Visual Question Answering
Chonghao Sima, Katrin Renz, Kashyap Chitta +7
We study how vision-language models (VLMs) trained on web-scale data can be integrated into end-to-end driving systems to boost generalization and enable interactivity with human u…
On Offline Evaluation of 3D Object Detection for Autonomous Driving
Tim Schreier, Katrin Renz, Andreas Geiger +1
Prior work in 3D object detection evaluates models using offline metrics like average precision since closed-loop online evaluation on the downstream driving task is costly. Howeve…
End-to-end Autonomous Driving: Challenges and Frontiers
Li Chen, Penghao Wu, Kashyap Chitta +3
The autonomous driving community has witnessed a rapid growth in approaches that embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle motion pl…
Parting with Misconceptions about Learning-based Vehicle Motion Planning
Daniel Dauner, Marcel Hallgarten, Andreas Geiger +1
The release of nuPlan marks a new era in vehicle motion planning research, offering the first large-scale real-world dataset and evaluation schemes requiring both precise short-ter…
Hidden Biases of End-to-End Driving Models
Bernhard Jaeger, Kashyap Chitta, Andreas Geiger
End-to-end driving systems have recently made rapid progress, in particular on CARLA. Independent of their major contribution, they introduce changes to minor system components. Co…