BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

Understand

While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent roadside cameras to extend the perception ability beyond the visual range.

• We discover that the state-of-the-art vision-centric bird's eye view detection methods have inferior performances on roadside cameras.
• This is because these methods mainly focus on recovering the depth regarding the camera center, where the depth difference between the car and the ground quickly shrinks while the distance increases.
• In this paper, we propose a simple yet effective approach, dubbed BEVHeight, to address this issue.