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Abstract

In this report, we present the 1st place solution for motion prediction track
in 2022 Waymo Open Dataset Challenges. We propose a novel Motion Transformer
framework for multimodal motion prediction, which introduces a small set of
novel motion query pairs for generating better multimodal future trajectories
by jointly performing the intention localization and iterative motion
refinement. A simple model ensemble strategy with non-maximum-suppression is
adopted to further boost the final performance. Our approach achieves the 1st
place on the motion prediction leaderboard of 2022 Waymo Open Dataset
Challenges, outperforming other methods with remarkable margins. Code will be
available at https://github.com/sshaoshuai/MTR.