3 papers
cs.CV2026
Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives
Lei Wan, Hannan Ejaz Keen, Alexey Vinel
Connected Autonomous Vehicles (CAVs) increasingly exploit Vehicle-to-Everything (V2X) communication to exchange multi-source sensor information, enabling advanced Collaborative Per…
cs.RO2026
VALISENS: A Validated Innovative Multi-Sensor System for Cooperative Automated Driving
Lei Wan, Prabesh Gupta, Andreas Eich +4
Reliable perception remains a key challenge for Connected Automated Vehicles (CAVs) in complex real-world environments, where varying lighting conditions and adverse weather degrad…
cs.CV2025
Systematic Literature Review on Vehicular Collaborative Perception -- A Computer Vision Perspective
Lei Wan, Jianxin Zhao, Andreas Wiedholz +7
The effectiveness of autonomous vehicles relies on reliable perception capabilities. Despite significant advancements in artificial intelligence and sensor fusion technologies, cur…