This report presents our Le3DE2E solution for unified sensor-based detection,
tracking, and forecasting in Argoverse Challenges at CVPR 2023 Workshop on
Autonomous Driving (WAD). We propose a unified network that incorporates three
tasks, including detection, tracking, and forecasting. This solution adopts a
strong Bird's Eye View (BEV) encoder with spatial and temporal fusion and
generates unified representations for multi-tasks. The solution was tested in
the Argoverse 2 sensor dataset to evaluate the detection, tracking, and
forecasting of 26 object categories. We achieved 1st place in Detection,
Tracking, and Forecasting on the E2E Forecasting track in Argoverse Challenges
at CVPR 2023 WAD.

我们的 Le3DE2E 解决方案用于统一的基于传感器的检测、跟踪和预测，在 CVPR 2023 无人驾驶研讨会（WAD）上的 Argoverse 挑战中展示。我们提出了一个统一的网络，包括检测、跟踪和预测三个任务。该解决方案采用了 Bird's Eye View（BEV）编码器，并进行了时空融合，生成用于多任务的统一表示。该解决方案在 Argoverse 2 传感器数据集上进行了测试，评估了 26 个物体类别的检测、跟踪和预测。我们在 Argoverse Challenges 的 E2E Forecasting 赛道上获得了检测、跟踪和预测的第一名。