THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling
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Abstract (arXiv)
In this paper, we propose THOMAS, a joint multi-agent trajectory prediction framework allowing for an efficient and consistent prediction of multi-agent multi-modal trajectories. We present a unified model architecture for simultaneous agent future heatmap estimation, in which we leverage hierarchical and sparse image generation for fast and memory-efficient inference. We propose a learnable trajectory recombination model that takes as input a set of predicted trajectories for each agent and outputs its consistent reordered recombination. This recombination module is able to realign the initially independent modalities so that they do no collide and are coherent with each other. We report our results on the Interaction multi-agent prediction challenge and rank 1st on the online test leaderboard.
Key facts. Cited by 101 papers in the map (data through 7 Oct 2026). Builds on 41 of its 49 references that are in the map. First posted on arXiv 13 Oct 2021.
Builds on
41 of 49 references.
References · 41
- 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
- 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
- 2018Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networkscited by 687
- 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 532
- 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 528
- 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
- 2020Learning Lane Graph Representations for Motion Forecastingcited by 380
- 2020TNT: Target-driveN Trajectory Predictioncited by 345
- 2021AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecastingcited by 327
- 2017DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agentscited by 310
- 2018SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraintscited by 296
- 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 292
29 more
- 2018Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networkscited by 289
- 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
- 2019INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Mapscited by 231
- 2018Convolutional Social Pooling for Vehicle Trajectory Predictioncited by 221
- 2019PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settingscited by 178
- 2019Multiple Futures Predictioncited by 178
- 2021GOHOME: Graph-Oriented Heatmap Output for future Motion Estimationcited by 146
- 2021HOME: Heatmap Output for future Motion Estimationcited by 122
- 2019Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactionscited by 117
- 2020Implicit Latent Variable Model for Scene-Consistent Motion Forecastingcited by 116
- 2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 112
- 2021Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversalscited by 112
- 2021LookOut: Diverse Multi-Future Prediction and Planning for Self-Drivingcited by 96
- 2021TPCN: Temporal Point Cloud Networks for Motion Forecastingcited by 94
- 2019Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecastingcited by 87
- 2018An LSTM Network for Highway Trajectory Predictioncited by 81
- 2020What-If Motion Prediction for Autonomous Drivingcited by 80
- 2020Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Planscited by 72
- 2021LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agentscited by 64
- 2021Learning to Predict Vehicle Trajectories with Model-based Planningcited by 63
- 2021Stepwise Goal-Driven Networks for Trajectory Predictioncited by 62
- 2020End-to-end Contextual Perception and Prediction with Interaction Transformercited by 54
- 2021Divide-and-Conquer for Lane-Aware Diverse Trajectory Predictioncited by 37
- 2020MATS: An Interpretable Trajectory Forecasting Representation for Planning and Controlcited by 30
- 2020Map-Adaptive Goal-Based Trajectory Predictioncited by 29
- 2020Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehiclescited by 28
- 2020ReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Predictioncited by 20
- 2020Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representationcited by 12
- 2021Asymmetrical Bi-RNN for pedestrian trajectory encodingcited by 6
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Citing papers per year: 2022: 19; 2023: 26; 2024: 28; 2025: 23; 2026: 5.
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