mlsanityData to 7 Oct 2026

TNT: Target-driveN Trajectory Prediction

arXiv 2008.08294 ↗First posted 19 Aug 2020cs.CV cs.ROcited by 345

Not on the map. Why?

Cited by 42 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Predicting the future behavior of moving agents is essential for real world applications. It is challenging as the intent of the agent and the corresponding behavior is unknown and intrinsically multimodal. Our key insight is that for prediction within a moderate time horizon, the future modes can be effectively captured by a set of target states. This leads to our target-driven trajectory prediction (TNT) framework. TNT has three stages which are trained end-to-end. It first predicts an agent's potential target states T steps into the future, by encoding its interactions with the environment and the other agents. TNT then generates trajectory state sequences conditioned on targets. A final stage estimates trajectory likelihoods and a final compact set of trajectory predictions is selected. This is in contrast to previous work which models agent intents as latent variables, and relies on test-time sampling to generate diverse trajectories. We benchmark TNT on trajectory prediction of vehicles and pedestrians, where we outperform state-of-the-art on Argoverse Forecasting, INTERACTION, Stanford Drone and an in-house Pedestrian-at-Intersection dataset.

Key facts. Cited by 345 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 43; 2022: 71; 2023: 76; 2024: 73; 2025: 53; 2026: 29.

345 papers.

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  1. 2022Planning-oriented Autonomous Drivingcited by 1,068
  2. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 532
  3. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Modelscited by 482
  4. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 292
  5. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networkscited by 279
  6. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 267
  7. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  8. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  9. 2022Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformercited by 211
  10. 2021Multimodal Motion Prediction with Stacked Transformerscited by 207
  11. 2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
  12. 2022Stochastic Trajectory Prediction via Motion Indeterminacy Diffusioncited by 184
38 more
  1. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectoriescited by 165
  2. 2023MotionLM: Multi-Agent Motion Forecasting as Language Modelingcited by 154
  3. 2022Model-Based Imitation Learning for Urban Drivingcited by 149
  4. 2021GOHOME: Graph-Oriented Heatmap Output for future Motion Estimationcited by 146
  5. 2023MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Queryingcited by 139
  6. 2022Learning from All Vehiclescited by 135
  7. 2021Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Predictioncited by 131
  8. 2021HOME: Heatmap Output for future Motion Estimationcited by 122
  9. 2025GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Drivingcited by 117
  10. 2022ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queriescited by 116
  11. 2023V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecastingcited by 114
  12. 2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 112
  13. 2021Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversalscited by 112
  14. 2022HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encodingcited by 109
  15. 2021THOMAS: Trajectory Heatmap Output with learned Multi-Agent Samplingcited by 101
  16. 2021LookOut: Diverse Multi-Future Prediction and Planning for Self-Drivingcited by 96
  17. 2021TPCN: Temporal Point Cloud Networks for Motion Forecastingcited by 94
  18. 2022M2I: From Factored Marginal Trajectory Prediction to Interactive Predictioncited by 81
  19. 2022BITS: Bi-level Imitation for Traffic Simulationcited by 80
  20. 2023Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoderscited by 72
  21. 2021SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policiescited by 68
  22. 2022GoRela: Go Relative for Viewpoint-Invariant Motion Forecastingcited by 68
  23. 2023FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Drivingcited by 67
  24. 2021LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agentscited by 64
  25. 2021Learning to Predict Vehicle Trajectories with Model-based Planningcited by 63
  26. 2021Stepwise Goal-Driven Networks for Trajectory Predictioncited by 62
  27. 2022MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Predictioncited by 59
  28. 2021LOKI: Long Term and Key Intentions for Trajectory Predictioncited by 57
  29. 2023TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Predictioncited by 56
  30. 2023LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraintscited by 50
  31. 2022GANet: Goal Area Network for Motion Forecastingcited by 49
  32. 2022StretchBEV: Stretching Future Instance Prediction Spatially and Temporallycited by 47
  33. 2023ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposalscited by 47
  34. 2023Leveraging Future Relationship Reasoning for Vehicle Trajectory Predictioncited by 47
  35. 2022Non-Probability Sampling Network for Stochastic Human Trajectory Predictioncited by 46
  36. 2024SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Drivingcited by 46
  37. 2023Traj-MAE: Masked Autoencoders for Trajectory Predictioncited by 42
  38. 2023EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecastingcited by 41

50 most cited of 345 All 345 (JSON)