论文标题
Waymo开放数据集挑战的第二名解决方案 - 2D对象检测
2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection
论文作者
论文摘要
实用的自主驾驶系统促使需要可靠，准确地检测车辆和人员。在本报告中，我们引入了一个最新的2D对象检测系统，用于自动驾驶方案。具体而言，我们将流行的两阶段探测器和一阶段检测器与无锚定时尚整合在一起，以产生强大的检测。此外，我们训练多个专家模型，并设计自动合奏方案的贪婪版本，该计划自动合并来自不同模型的检测。值得注意的是，我们的总体检测系统在Waymo Open DataSet V1.2上实现了70.28 L2 MAP，在Waymo Open DataSet挑战的2D检测轨道中排名第二。
A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons. In this report, we introduce a state-of-the-art 2D object detection system for autonomous driving scenarios. Specifically, we integrate both popular two-stage detector and one-stage detector with anchor free fashion to yield a robust detection. Furthermore, we train multiple expert models and design a greedy version of the auto ensemble scheme that automatically merges detections from different models. Notably, our overall detection system achieves 70.28 L2 mAP on the Waymo Open Dataset v1.2, ranking the 2nd place in the 2D detection track of the Waymo Open Dataset Challenges.
