activity
20242026
most citedAMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detection

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

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV20262 cited

AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detection

Zizhao Chen, Yeqiang Qian, Xiaoxiao Yang +2

Multispectral pedestrian detection has been shown to be effective in improving performance within complex illumination scenarios. However, prevalent double-stream networks in multi…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…