2 citations · 3 across the 5 of their papers we have counts for
5 papers
MapFusion: A Novel BEV Feature Fusion Network for Multi-modal Map Construction
Xiaoshuai Hao, Yunfeng Diao, Mengchuan Wei +7
Map construction task plays a vital role in providing precise and comprehensive static environmental information essential for autonomous driving systems. Primary sensors include c…
Is Your HD Map Constructor Reliable under Sensor Corruptions?
Xiaoshuai Hao, Mengchuan Wei, Yifan Yang +7
Driving systems often rely on high-definition (HD) maps for precise environmental information, which is crucial for planning and navigation. While current HD map constructors perfo…
The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition
Lingdong Kong, Shaoyuan Xie, Hanjiang Hu +88
In the realm of autonomous driving, robust perception under out-of-distribution conditions is paramount for the safe deployment of vehicles. Challenges such as adverse weather, sen…
Team Samsung-RAL: Technical Report for 2024 RoboDrive Challenge-Robust Map Segmentation Track
Xiaoshuai Hao, Yifan Yang, Hui Zhang +4
In this report, we describe the technical details of our submission to the 2024 RoboDrive Challenge Robust Map Segmentation Track. The Robust Map Segmentation track focuses on the…
HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction
Yi Zhou, Hui Zhang, Jiaqian Yu +4
Vectorized High-Definition (HD) map construction requires predictions of the category and point coordinates of map elements (e.g. road boundary, lane divider, pedestrian crossing,…