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cs.CV2026
From Features to Reference Points: Lightweight and Adaptive Fusion for Cooperative Autonomous Driving
Yongqi Zhu, Morui Zhu, Qi Chen +4
We present RefPtsFusion, a lightweight and interpretable framework for cooperative autonomous driving. Instead of sharing large feature maps or query embeddings, vehicles exchange…
cs.CV2024
HEAD: A Bandwidth-Efficient Cooperative Perception Approach for Heterogeneous Connected and Autonomous Vehicles
Deyuan Qu, Qi Chen, Yongqi Zhu +4
In cooperative perception studies, there is often a trade-off between communication bandwidth and perception performance. While current feature fusion solutions are known for their…
cs.CV2024
SiCP: Simultaneous Individual and Cooperative Perception for 3D Object Detection in Connected and Automated Vehicles
Deyuan Qu, Qi Chen, Tianyu Bai +5
Cooperative perception for connected and automated vehicles is traditionally achieved through the fusion of feature maps from two or more vehicles. However, the absence of feature…