MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge -- Motion Prediction

• URL: http://arxiv.org/abs/2209.10033v1
• Date: Tue, 20 Sep 2022 23:03:22 GMT
• Title: MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge -- Motion Prediction
• Authors: Shaoshuai Shi, Li Jiang, Dengxin Dai, Bernt Schiele
• Abstract summary: We propose a novel Motion Transformer framework for multimodal motion prediction, which introduces a small set of novel motion query pairs. 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 Open dataset Challenges, outperforming other methods with remarkable margins.
• Score: 103.75625476231401
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

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