Technical Report for Argoverse Challenges on Unified Sensor-based
  Detection, Tracking, and Forecasting
Zhepeng Wang Feng Chen Kanokphan Lertniphonphan Siwei Chen Jinyao Bao Pengfei Zheng Jinbao Zhang Kaer Huang Tao Zhang
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.