7 papers
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…
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…
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…
MapDistill: Boosting Efficient Camera-based HD Map Construction via Camera-LiDAR Fusion Model Distillation
Xiaoshuai Hao, Ruikai Li, Hui Zhang +7
Online high-definition (HD) map construction is an important and challenging task in autonomous driving. Recently, there has been a growing interest in cost-effective multi-view ca…
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…
UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weather
Haimei Zhao, Jing Zhang, Zhuo Chen +2
LiDAR semantic segmentation (LSS) is a critical task in autonomous driving and has achieved promising progress. However, prior LSS methods are conventionally investigated and evalu…