AIR^2 for Interaction Prediction

Code

• github.com/david9dragon9/air
  OfficialIn papertf★ 22

Abstract

The 2021 Waymo Interaction Prediction Challenge introduced a problem of predicting the future trajectories and confidences of two interacting agents jointly. We developed a solution that takes an anchored marginal motion prediction model with rasterization and augments it to model agent interaction. We do this by predicting the joint confidences using a rasterized image that highlights the ego agent and the interacting agent. Our solution operates on the cartesian product space of the anchors; hence the "^2" in AIR^2. Our model achieved the highest mAP (the primary metric) on the leaderboard.

Tasks

Reproductions