6 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…
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…
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…
A Concise Survey on Lane Topology Reasoning for HD Mapping
Yi Yao, Miao Fan, Shengtong Xu +4
Lane topology reasoning techniques play a crucial role in high-definition (HD) mapping and autonomous driving applications. While recent years have witnessed significant advances i…
Video-based Traffic Light Recognition by Rockchip RV1126 for Autonomous Driving
Miao Fan, Xuxu Kong, Shengtong Xu +2
Real-time traffic light recognition is fundamental for autonomous driving safety and navigation in urban environments. While existing approaches rely on single-frame analysis from…
A Benchmark for Vision-Centric HD Mapping by V2I Systems
Miao Fan, Shanshan Yu, Shengtong Xu +3
Autonomous driving faces safety challenges due to a lack of global perspective and the semantic information of vectorized high-definition (HD) maps. Information from roadside camer…