MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views

Understand

Autonomous driving requires the inference of actionable information such as detecting and classifying objects, and determining the drivable space.

• To this end, we present Multi-View LidarNet (MVLidarNet), a two-stage deep neural network for multi-class object detection and drivable space segmentation using multiple views of a single LiDAR point cloud.
• The first stage processes the point cloud projected onto a perspective view in order to semantically segment the scene.
• The second stage then processes the point cloud (along with semantic labels from the first stage) projected onto a bird's eye view, to detect and classify objects.