mlsanityData to 7 Oct 2026

TPCN: Temporal Point Cloud Networks for Motion Forecasting

arXiv 2103.03067 ↗First posted 4 Mar 2021cs.CV cs.ROcited by 94

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Abstract (arXiv)

We propose the Temporal Point Cloud Networks (TPCN), a novel and flexible framework with joint spatial and temporal learning for trajectory prediction. Unlike existing approaches that rasterize agents and map information as 2D images or operate in a graph representation, our approach extends ideas from point cloud learning with dynamic temporal learning to capture both spatial and temporal information by splitting trajectory prediction into both spatial and temporal dimensions. In the spatial dimension, agents can be viewed as an unordered point set, and thus it is straightforward to apply point cloud learning techniques to model agents' locations. While the spatial dimension does not take kinematic and motion information into account, we further propose dynamic temporal learning to model agents' motion over time. Experiments on the Argoverse motion forecasting benchmark show that our approach achieves the state-of-the-art results.

Key facts. Cited by 94 papers in the map (data through 7 Oct 2026). Builds on 31 of its 38 references that are in the map. First posted on arXiv 4 Mar 2021.

Builds on

31 of 38 references.

References · 31

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  4. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  5. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  6. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,447
  7. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,202
  8. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 890
  9. 2015Convolutional Networks on Graphs for Learning Molecular Fingerprintscited by 751
  10. 20173D Semantic Segmentation with Submanifold Sparse Convolutional Networkscited by 746
  11. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
  12. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 528
19 more
  1. 2020Searching Efficient 3D Architectures with Sparse Point-Voxel Convolutioncited by 422
  2. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
  3. 2018ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worstcited by 391
  4. 2020Learning Lane Graph Representations for Motion Forecastingcited by 380
  5. 2020TNT: Target-driveN Trajectory Predictioncited by 345
  6. 2019Point-Voxel CNN for Efficient 3D Deep Learningcited by 343
  7. 2020Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Predictioncited by 324
  8. 2018Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networkscited by 289
  9. 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
  10. 2015Deep Convolutional Networks on Graph-Structured Datacited by 246
  11. 2021End-to-end Interpretable Neural Motion Plannercited by 240
  12. 2020It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Predictioncited by 235
  13. 2020Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Netcited by 228
  14. 2018Acquisition of Localization Confidence for Accurate Object Detectioncited by 174
  15. 2021IntentNet: Learning to Predict Intention from Raw Sensor Datacited by 158
  16. 2019Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecastingcited by 87
  17. 2020HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detectioncited by 82
  18. 2020TPNet: Trajectory Proposal Network for Motion Predictioncited by 80
  19. 2018Interaction-Aware Probabilistic Behavior Prediction in Urban Environmentscited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 23; 2023: 31; 2024: 17; 2025: 10; 2026: 2.

94 papers.

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  1. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 292
  2. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 267
  3. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  4. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectoriescited by 165
  5. 2021GOHOME: Graph-Oriented Heatmap Output for future Motion Estimationcited by 146
  6. 2023MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Queryingcited by 139
  7. 2021HOME: Heatmap Output for future Motion Estimationcited by 122
  8. 2022HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encodingcited by 109
  9. 2021THOMAS: Trajectory Heatmap Output with learned Multi-Agent Samplingcited by 101
  10. 2023Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Surveycited by 101
  11. 2023Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoderscited by 72
  12. 2022Motion Inspired Unsupervised Perception and Prediction in Autonomous Drivingcited by 59
38 more
  1. 2023LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraintscited by 50
  2. 2022GANet: Goal Area Network for Motion Forecastingcited by 49
  3. 2023ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposalscited by 47
  4. 2023Leveraging Future Relationship Reasoning for Vehicle Trajectory Predictioncited by 47
  5. 2023Traj-MAE: Masked Autoencoders for Trajectory Predictioncited by 42
  6. 2022FJMP: Factorized Joint Multi-Agent Motion Prediction over Learned Directed Acyclic Interaction Graphscited by 41
  7. 2023ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptationcited by 39
  8. 2024HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attentioncited by 37
  9. 2023PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Drivingcited by 33
  10. 2023MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Predictioncited by 32
  11. 2022SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Drivingcited by 31
  12. 2023BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous Drivingcited by 28
  13. 2023Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networkscited by 27
  14. 2023Advancements in Point Cloud Data Augmentation for Deep Learning: A Surveycited by 24
  15. 2021DRINet++: Efficient Voxel-as-point Point Cloud Segmentationcited by 23
  16. 2022Path-Aware Graph Attention for HD Maps in Motion Predictioncited by 23
  17. 2022Bootstrap Motion Forecasting With Self-Consistent Constraintscited by 23
  18. 2022R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinementcited by 23
  19. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
  20. 2023LiDAR-based 4D Occupancy Completion and Forecastingcited by 23
  21. 2022CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attentioncited by 21
  22. 2022LatentFormer: Multi-Agent Transformer-Based Interaction Modeling and Trajectory Predictioncited by 19
  23. 2023DICE: Diverse Diffusion Model with Scoring for Trajectory Predictioncited by 18
  24. 2021Collaborative Uncertainty in Multi-Agent Trajectory Forecastingcited by 17
  25. 2023EDA: Evolving and Distinct Anchors for Multimodal Motion Predictioncited by 17
  26. 2025Trajectory Mamba: Efficient Attention-Mamba Forecasting Model Based on Selective SSMcited by 17
  27. 2021Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Drivingcited by 15
  28. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  29. 2022Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecastingcited by 13
  30. 2023SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentationcited by 13
  31. 2024AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Drivingcited by 13
  32. 2024MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Drivingcited by 12
  33. 2021Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modelingcited by 11
  34. 2022TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictorcited by 10
  35. 2022Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecastingcited by 10
  36. 2022Trajectory Forecasting from Detection with Uncertainty-Aware Motion Encodingcited by 8
  37. 2022Holistic Transformer: A Joint Neural Network for Trajectory Prediction and Decision-Making of Autonomous Vehiclescited by 8
  38. 2022Aware of the History: Trajectory Forecasting with the Local Behavior Datacited by 8

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