mlsanityData to 14 Oct 2026

GANet: Goal Area Network for Motion Forecasting

arXiv 2209.09723 ↗First posted 20 Sep 2022cs.CVcited by 49

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Abstract (arXiv)

Predicting the future motion of road participants is crucial for autonomous driving but is extremely challenging due to staggering motion uncertainty. Recently, most motion forecasting methods resort to the goal-based strategy, i.e., predicting endpoints of motion trajectories as conditions to regress the entire trajectories, so that the search space of solution can be reduced. However, accurate goal coordinates are hard to predict and evaluate. In addition, the point representation of the destination limits the utilization of a rich road context, leading to inaccurate prediction results in many cases. Goal area, i.e., the possible destination area, rather than goal coordinate, could provide a more soft constraint for searching potential trajectories by involving more tolerance and guidance. In view of this, we propose a new goal area-based framework, named Goal Area Network (GANet), for motion forecasting, which models goal areas rather than exact goal coordinates as preconditions for trajectory prediction, performing more robustly and accurately. Specifically, we propose a GoICrop (Goal Area of Interest) operator to effectively extract semantic lane features in goal areas and model actors' future interactions, which benefits a lot for future trajectory estimations. GANet ranks the 1st on the leaderboard of Argoverse Challenge among all public literature (till the paper submission), and its source codes will be released.

Key facts. Cited by 49 papers in the map (data through 14 Oct 2026). Builds on 25 of its 32 references that are in the map. First posted on arXiv 20 Sep 2022.

Builds on

25 of 32 references.

References · 25

  1. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 732
  2. 2018Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networkscited by 690
  3. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 537
  4. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 530
  5. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 420
  6. 2020Learning Lane Graph Representations for Motion Forecastingcited by 382
  7. 2020TNT: Target-driveN Trajectory Predictioncited by 347
  8. 2017DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agentscited by 310
  9. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 295
  10. 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
  11. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  12. 2021Multimodal Motion Prediction with Stacked Transformerscited by 208
13 more
  1. 2021IntentNet: Learning to Predict Intention from Raw Sensor Datacited by 158
  2. 2021GOHOME: Graph-Oriented Heatmap Output for future Motion Estimationcited by 146
  3. 2021HOME: Heatmap Output for future Motion Estimationcited by 122
  4. 2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 113
  5. 2019SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Predictioncited by 111
  6. 2021THOMAS: Trajectory Heatmap Output with learned Multi-Agent Samplingcited by 101
  7. 2021TPCN: Temporal Point Cloud Networks for Motion Forecastingcited by 94
  8. 2019Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecastingcited by 87
  9. 2021Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Drivingcited by 73
  10. 2020Map-Adaptive Goal-Based Trajectory Predictioncited by 30
  11. 2022Bootstrap Motion Forecasting With Self-Consistent Constraintscited by 23
  12. 2022TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Predictioncited by 14
  13. 2022KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long-Term Trajectory Predictioncited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 12; 2024: 20; 2025: 9; 2026: 7.

49 papers.

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  1. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 707
  2. 2023Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoderscited by 73
  3. 2023Leveraging Future Relationship Reasoning for Vehicle Trajectory Predictioncited by 48
  4. 2023Traj-MAE: Masked Autoencoders for Trajectory Predictioncited by 42
  5. 2024HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attentioncited by 38
  6. 2024SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Predictioncited by 34
  7. 2023MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Predictioncited by 32
  8. 2022Behavioral Intention Prediction in Driving Scenes: A Surveycited by 30
  9. 2024Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioningcited by 30
  10. 2023SEPT: Towards Efficient Scene Representation Learning for Motion Predictioncited by 27
  11. 2023Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?cited by 22
  12. 2025Trajectory Mamba: Efficient Attention-Mamba Forecasting Model Based on Selective SSMcited by 18
37 more
  1. 2024AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Drivingcited by 13
  2. 2024Motion Forecasting in Continuous Drivingcited by 11
  3. 2023Vision-based Multi-future Trajectory Prediction: A Surveycited by 8
  4. 2023CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Drivingcited by 8
  5. 2024Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarkingcited by 8
  6. 2024TrACT: A Training Dynamics Aware Contrastive Learning Framework for Long-tail Trajectory Predictioncited by 7
  7. 2025DONUT: A Decoder-Only Model for Trajectory Predictioncited by 7
  8. 2025GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Predictioncited by 7
  9. 2024FutureNet-LOF: Joint Trajectory Prediction and Lane Occupancy Field Prediction with Future Context Encodingcited by 6
  10. 2024Multi-Agent Trajectory Prediction with Difficulty-Guided Feature Enhancement Networkcited by 6
  11. 2023Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictionscited by 5
  12. 2025Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planningcited by 5
  13. 2024Annealed Winner-Takes-All for Motion Forecastingcited by 4
  14. 2025Future-Aware Interaction Network For Motion Forecastingcited by 4
  15. 2023FFINet: Future Feedback Interaction Network for Motion Forecastingcited by 3
  16. 2024ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Drivingcited by 3
  17. 2024DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Drivingcited by 3
  18. 2024ESP: Extro-Spective Prediction for Long-term Behavior Reasoning in Emergency Scenarioscited by 3
  19. 2024Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Modelscited by 3
  20. 2024A Structure-Aware Lane Graph Transformer Model for Vehicle Trajectory Predictioncited by 2
  21. 2024CCF: Cross Correcting Framework for Pedestrian Trajectory Predictioncited by 2
  22. 2024Diving Deeper Into Pedestrian Behavior Understanding: Intention Estimation, Action Prediction, and Event Risk Assessmentcited by 2
  23. 2024PPT: Pretraining with Pseudo-Labeled Trajectories for Motion Forecastingcited by 2
  24. 2025HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learningcited by 2
  25. 2026Recover to Predict: Progressive Retrospective Learning for Variable-Length Trajectory Predictioncited by 2
  26. 2023MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehiclescited by 1
  27. 2024PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Networkcited by 1
  28. 2024Multi-modal Motion Prediction using Temporal Ensembling with Learning-based Aggregationcited by 1
  29. 2025LANet: A Lane Boundaries-Aware Approach For Robust Trajectory Predictioncited by 1
  30. 2026Streaming Real-Time Trajectory Prediction Using Endpoint-Aware Modelingcited by 1
  31. 2025ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capturecited by 0
  32. 2025Ensemble of Pre-Trained Models for Long-Tailed Trajectory Predictioncited by 0
  33. 2026FoSS: Modeling Long Range Dependencies and Multimodal Uncertainty in Trajectory Prediction via Fourier State Space Integrationcited by 0
  34. 2026TaPD: Temporal-adaptive Progressive Distillation for Observation-Adaptive Trajectory Forecasting in Autonomous Drivingcited by 0
  35. 2026SHARP: Short-Window Streaming for Accurate and Robust Prediction in Motion Forecastingcited by 0
  36. 2026Reasonable Motion: A General ASP Foundation for Environment Constrained Movement Trajectory Computationcited by 0
  37. 2026A Unified Framework for Trajectory Prediction with Explicit Planning and Reaction Decompositioncited by 0