collaborators

5 papers

cs.CV2025

Delving into Mapping Uncertainty for Mapless Trajectory Prediction

Zongzheng Zhang, Xuchong Qiu, Boran Zhang +11

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 e…

cs.CV2025

Reusing Attention for One-stage Lane Topology Understanding

Yang Li, Zongzheng Zhang, Xuchong Qiu +10

Understanding lane toplogy relationships accurately is critical for safe autonomous driving. However, existing two-stage methods suffer from inefficiencies due to error propagation…

cs.CV2025

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models

Haohan Chi, Huan-ang Gao, Ziming Liu +12

Vision-Language-Action (VLA) models for autonomous driving show promise but falter in unstructured corner case scenarios, largely due to a scarcity of targeted benchmarks. To addre…

cs.CV2025

Control Map Distribution using Map Query Bank for Online Map Generation

Ziming Liu, Leichen Wang, Ge Yang +4

Reliable autonomous driving systems require high-definition (HD) map that contains detailed map information for planning and navigation. However, pre-build HD map requires a large…

cs.CV2025

Chameleon: Fast-slow Neuro-symbolic Lane Topology Extraction

Zongzheng Zhang, Xinrun Li, Sizhe Zou +8

Lane topology extraction involves detecting lanes and traffic elements and determining their relationships, a key perception task for mapless autonomous driving. This task requires…