PIXOR: Real-time 3D Object Detection from Point Clouds

November 2020

tl;dr: Voxelize point cloud into 3D occupancy grid for lidar 3D object detection.

Overall impression

The paper has a super simple architecture for lidar-only 3D object detection in BEV (3D object localization). This representation is also used in PIXOR++ and FaF.

The paper reminds me of the wave of anchor free papers in 2019Q1 such as CenterNet and FCOS. Note that PIXOR still uses decoded box based NMS.

After two years in publication, it is still one of the fastest lidar object detection model out there (33 Hz). It is further improved in PIXOR++.

This paper is from Uber’s Toronto team, and is superseded by LaserNet, also from Uber but from the Pittsburg team.

Key ideas

Technical details