mlsanityData to 14 Oct 2026

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

arXiv 2207.00170 ↗First posted 30 Jun 2022cs.CV cs.AIcited by 14

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Abstract (arXiv)

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

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 30 Jun 2022.

Builds on

5 of 13 references.

References · 5

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2020End-to-End Object Detection with Transformerscited by 7,414
  3. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  4. 2020On Layer Normalization in the Transformer Architecturecited by 922
  5. 2016Stochastic Multiple Choice Learning for Training Diverse Deep Ensemblescited by 77

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Cited by year

Citing papers per year: 2022: 4; 2023: 7; 2024: 3.

14 papers.

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  1. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 270
  2. 2023MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Queryingcited by 140
  3. 2022GoRela: Go Relative for Viewpoint-Invariant Motion Forecastingcited by 68
  4. 2022GANet: Goal Area Network for Motion Forecastingcited by 49
  5. 2023ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposalscited by 48
  6. 2023Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encodingcited by 33
  7. 2023The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Reviewcited by 29
  8. 2024GMMFormer v2: An Uncertainty-aware Framework for Partially Relevant Video Retrievalcited by 12
  9. 2024Motion Forecasting in Continuous Drivingcited by 11
  10. 2023PBP: Path-based Trajectory Prediction for Autonomous Drivingcited by 6
  11. 2024Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecastingcited by 4
  12. 2023FFINet: Future Feedback Interaction Network for Motion Forecastingcited by 3
2 more
  1. 2022Improving Motion Forecasting for Autonomous Driving with the Cycle Consistency Losscited by 1
  2. 2023Enhancing Trajectory Prediction through Self-Supervised Waypoint Noise Predictioncited by 1