1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
This work addresses object detection for autonomous driving, but it is incremental as it builds on existing methods.
The authors tackled the 2D object detection problem on the Waymo Open Dataset, achieving first place by using FPN with enhancements like Cascade RCNN and large image scales to handle small objects.
In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track. We adopt FPN as our basic framework. Cascade RCNN, stacked PAFPN Neck and Double-Head are used for performance improvements. In order to handle the small object detection problem in WOD, we use very large image scales for both training and testing. Using our methods, our team RW-TSDet achieved the 1st place in the 2D Object Detection Track.