论文标题
Waymo开放数据集挑战2020-2D对象检测轨道的第一名解决方案
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
论文作者
论文摘要
在此技术报告中，我们介绍了Waymo Open Datatet（WOD）挑战2020-2D对象轨迹的解决方案。我们采用FPN作为我们的基本框架。级联RCNN，堆叠的PAFPN颈部和双头用于改进性能。为了处理WOD中的小物体检测问题，我们使用非常大的图像量表进行训练和测试。使用我们的方法，我们的RW-TSDET团队在2D对象检测轨道中获得了第一名。
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.
