9 papers
SGAD: Semantic and Geometric-aware Descriptor for Local Feature Matching
Xiangzeng Liu, Chi Wang, Guanglu Shi +3
Local feature matching remains a fundamental challenge in computer vision. Recent Area to Point Matching (A2PM) methods have improved matching accuracy. However, existing research…
Traffic Signal Phase and Timing Estimation with Large-Scale Floating Car Data
Mingcheng Liao, Zebang Feng, Miao Fan +2
Effective modern transportation systems depend critically on accurate Signal Phase and Timing (SPaT) estimation. However, acquiring ground-truth SPaT information faces significant…
Multimodal HD Mapping for Intersections by Intelligent Roadside Units
Zhongzhang Chen, Miao Fan, Shengtong Xu +4
High-definition (HD) semantic mapping of complex intersections poses significant challenges for traditional vehicle-based approaches due to occlusions and limited perspectives. Thi…
End-to-End Generation of City-Scale Vectorized Maps by Crowdsourced Vehicles
Zebang Feng, Miao Fan, Bao Liu +2
High-precision vectorized maps are indispensable for autonomous driving, yet traditional LiDAR-based creation is costly and slow, while single-vehicle perception methods lack accur…
Learning to Generate Vectorized Maps at Intersections with Multiple Roadside Cameras
Quanxin Zheng, Miao Fan, Shengtong Xu +2
Vectorized maps are indispensable for precise navigation and the safe operation of autonomous vehicles. Traditional methods for constructing these maps fall into two categories: of…
Semantic SLAM with Rolling-Shutter Cameras and Low-Precision INS in Outdoor Environments
Yuchen Zhang, Miao Fan, Shengtong Xu +2
Accurate localization and mapping in outdoor environments remains challenging when using consumer-grade hardware, particularly with rolling-shutter cameras and low-precision inerti…