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20242026
most citedIntegrating Multi-Modal Sensors: A Review of Fusion Techniques for Intelligent Vehicles

24 citations · 26 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

DriveMotion: A Large-Scale Multi-Source Benchmark for Driver Motion Sequence Modeling and Forecasting

Yuhang Wang, Chuheng Wei, Jingxin Yang +2

Driver motion can provide cues to ongoing behavior, attention, and near-term driving intent. However, most existing driver-centric datasets focus on recognizing predefined driver b…

cs.CV2026

A Multi-modal Detection System for Infrastructure-based Freight Signal Priority

Ziyan Zhang, Chuheng Wei, Xuanpeng Zhao +6

Freight vehicles approaching signalized intersections require reliable detection and motion estimation to support infrastructure-based Freight Signal Priority (FSP). Accurate and t…

cs.CV20251 cited

HeCoFuse: Cross-Modal Complementary V2X Cooperative Perception with Heterogeneous Sensors

Chuheng Wei, Ziye Qin, Walter Zimmer +2

Real-world Vehicle-to-Everything (V2X) cooperative perception systems often operate under heterogeneous sensor configurations due to cost constraints and deployment variability acr…

cs.CV202524 cited

Integrating Multi-Modal Sensors: A Review of Fusion Techniques for Intelligent Vehicles

Chuheng Wei, Ziye Qin, Ziyan Zhang +2

Multi-sensor fusion plays a critical role in enhancing perception for autonomous driving, overcoming individual sensor limitations, and enabling comprehensive environmental underst…

cs.CV2025

PDB: Not All Drivers Are the Same -- A Personalized Dataset for Understanding Driving Behavior

Chuheng Wei, Ziye Qin, Siyan Li +7

Driving behavior is inherently personal, influenced by individual habits, decision-making styles, and physiological states. However, most existing datasets treat all drivers as hom…

cs.CV2024

Feature Corrective Transfer Learning: End-to-End Solutions to Object Detection in Non-Ideal Visual Conditions

Chuheng Wei, Guoyuan Wu, Matthew J. Barth

A significant challenge in the field of object detection lies in the system's performance under non-ideal imaging conditions, such as rain, fog, low illumination, or raw Bayer imag…