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This technical report presents an effective method for motion prediction inautonomous driving. We develop a Transformer-based method for input encodingand trajectory prediction. Besides, we propose the Temporal Flow Header toenhance the trajectory encoding. In the end, an efficient K-means ensemblemethod is used. Using our Transformer network and ensemble method, we win thefirst place of Argoverse 2 Motion Forecasting Challenge with thestate-of-the-art brier-minFDE score of 1.90.

TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction