VI-BEV: Vehicle-Infrastructure Collaborative Perception for 3-D Object Detection on Bird’s-Eye View

As infrastructure equipment development matures, leveraging these assets to enhance automated vehicle perception becomes increasingly valuable for more accurate and broader 3D object detection. This paper proposes a straightforward and scalable framework to incorporate infrastructure and vehicle onb...

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Bibliographic Details
Main Authors: Jingxiong Meng, Junfeng Zhao
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
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Online Access:https://ieeexplore.ieee.org/document/10896690/
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Summary:As infrastructure equipment development matures, leveraging these assets to enhance automated vehicle perception becomes increasingly valuable for more accurate and broader 3D object detection. This paper proposes a straightforward and scalable framework to incorporate infrastructure and vehicle onboard sensors to perform 3D object detection on Bird’s Eye View(BEV) images. And a cross-attention based block is involved in utilizing the interacted information among the sensors for sensor information fusion. Our model gets validated on the online V2X-Sim dataset under two scenarios: the short-range case and the long-range case. Our model demonstrates superior accuracy and broader detection capabilities compared to the baseline model from the experiment results.
ISSN:2687-7813