57 citations · 196 across the 11 of their papers we have counts for
5 papers · 1 filter
Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking
Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado +4
Panoptic scene understanding and tracking of dynamic agents are essential for robots and automated vehicles to navigate in urban environments. As LiDARs provide accurate illuminati…
The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior
Bassam Helou, Aditya Dusi, Anne Collin +7
Autonomous vehicles must balance a complex set of objectives. There is no consensus on how they should do so, nor on a model for specifying a desired driving behavior. We created a…
Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals
Nachiket Deo, Eric M. Wolff, Oscar Beijbom
Accurately predicting the future motion of surrounding vehicles requires reasoning about the inherent uncertainty in driving behavior. This uncertainty can be loosely decoupled int…
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan +6
In this work, we propose the world's first closed-loop ML-based planning benchmark for autonomous driving. While there is a growing body of ML-based motion planners, the lack of es…
PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillars
Qi Chen, Sourabh Vora, Oscar Beijbom
Recent works recognized lidars as an inherently streaming data source and showed that the end-to-end latency of lidar perception models can be reduced significantly by operating on…