7 papers
RadarXFormer: Robust Object Detection via Cross-Dimension Fusion of 4D Radar Spectra and Images for Autonomous Driving
Yue Sun, Yeqiang Qian, Zhe Wang +3
Reliable perception is essential for autonomous driving systems to operate safely under diverse real-world traffic conditions. However, camera- and LiDAR-based perception systems s…
Which LiDAR scanning pattern is better for roadside perception: Repetitive or Non-repetitive?
Zhiqi Qi, Runxin Zhao, Hanyang Zhuang +2
LiDAR-based roadside perception is a cornerstone of advanced Intelligent Transportation Systems (ITS). While considerable research has addressed optimal LiDAR placement for infrast…
Bench-RNR: Dataset for Benchmarking Repetitive and Non-repetitive Scanning LiDAR for Infrastructure-based Vehicle Localization
Runxin Zhao, Chunxiang Wang, Hanyang Zhuang +1
Vehicle localization using roadside LiDARs can provide centimeter-level accuracy for cloud-controlled vehicles while simultaneously serving multiple vehicles, enhanc-ing safety and…
Weather-Magician: Reconstruction and Rendering Framework for 4D Weather Synthesis In Real Time
Chen Sang, Yeqiang Qian, Jiale Zhang +2
For tasks such as urban digital twins, VR/AR/game scene design, or creating synthetic films, the traditional industrial approach often involves manually modeling scenes and using v…
Depth-aware Fusion Method based on Image and 4D Radar Spectrum for 3D Object Detection
Yue Sun, Yeqiang Qian, Chunxiang Wang +1
Safety and reliability are crucial for the public acceptance of autonomous driving. To ensure accurate and reliable environmental perception, intelligent vehicles must exhibit accu…
Cross-Modal Visual Relocalization in Prior LiDAR Maps Utilizing Intensity Textures
Qiyuan Shen, Hengwang Zhao, Weihao Yan +3
Cross-modal localization has drawn increasing attention in recent years, while the visual relocalization in prior LiDAR maps is less studied. Related methods usually suffer from in…