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

2 citations · 2 across the 2 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.RO20252 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

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…