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

Abstract

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.