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Xunjiang Gu

4 accepted papers

2025

Delving into Mapping Uncertainty for Mapless Trajectory Prediction

IROS 2025

Recent advances in autonomous driving are moving towards mapless approaches, where High-Definition (HD) maps are generated online directly from sensor data, reducing the need for expensive labeling and maintenance. However, the reliability of these online-generated maps remains uncertain. While inco

Cited by 4SourcecodeScholar
2025

Pseudo-Simulation for Autonomous Driving

CoRL 2025poster

Existing evaluation paradigms for Autonomous Vehicles (AVs) face critical limitations. Real-world evaluation is often challenging due to safety concerns and a lack of reproducibility, whereas closed-loop simulation can face insufficient realism or high computational costs. Open-loop evaluation, whil…

Cited by 0SourcecodeScholar
2024

Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention

ECCV 2024poster

"Understanding road geometry is a critical component of the autonomous vehicle (AV) stack. While high-definition (HD) maps can readily provide such information, they suffer from high labeling and maintenance costs. Accordingly, many recent works have proposed methods for estimating HD maps online fr…

2024

Producing and Leveraging Online Map Uncertainty in Trajectory Prediction

CVPR 2024poster

High-definition (HD) maps have played an integral role in the development of modern autonomous vehicle (AV) stacks albeit with high associated labeling and maintenance costs. As a result many recent works have proposed methods for estimating HD maps online from sensor data enabling AVs to operate ou…