most citedMSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

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…

cs.RO2025★ 2 cited

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Xiaoshuai Hao, Guanqun Liu, Yuting Zhao +6

Multi-sensor fusion models play a crucial role in autonomous driving perception, particularly in tasks like 3D object detection and HD map construction. These models provide essent…

cs.RO2024★ 2 cited

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…

cs.CV2024

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…

cs.CV2024

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…