mlsanityData to 7 Oct 2026

Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference Speed

arXiv 2409.16154 ↗First posted 24 Sep 2024cs.RO cs.CVcited by 9

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Abstract (arXiv)

For efficient and safe autonomous driving, it is essential that autonomous vehicles can predict the motion of other traffic agents. While highly accurate, current motion prediction models often impose significant challenges in terms of training resource requirements and deployment on embedded hardware. We propose a new efficient motion prediction model, which achieves highly competitive benchmark results while training only a few hours on a single GPU. Due to our lightweight architectural choices and the focus on reducing the required training resources, our model can easily be applied to custom datasets. Furthermore, its low inference latency makes it particularly suitable for deployment in autonomous applications with limited computing resources.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 31 of its 35 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

31 of 35 references.

References · 31

  1. 2020End-to-End Object Detection with Transformerscited by 7,384
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  4. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 728
  5. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  6. 2021Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetcited by 532
  7. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
  8. 2020Learning Lane Graph Representations for Motion Forecastingcited by 380
  9. 2021Pay Attention to MLPscited by 367
  10. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networkscited by 279
  11. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 267
  12. 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
19 more
  1. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  2. 2022Neighborhood Attention Transformercited by 235
  3. 2021Multimodal Motion Prediction with Stacked Transformerscited by 207
  4. 2017Social Attention: Modeling Attention in Human Crowdscited by 185
  5. 2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 112
  6. 2021THOMAS: Trajectory Heatmap Output with learned Multi-Agent Samplingcited by 101
  7. 2019Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecastingcited by 87
  8. 2023Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoderscited by 72
  9. 2022GoRela: Go Relative for Viewpoint-Invariant Motion Forecastingcited by 68
  10. 2020End-to-end Contextual Perception and Prediction with Interaction Transformercited by 54
  11. 2023ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposalscited by 47
  12. 2023Leveraging Future Relationship Reasoning for Vehicle Trajectory Predictioncited by 47
  13. 2023ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptationcited by 39
  14. 2023MacFormer: Map-Agent Coupled Transformer for Real-time and Robust Trajectory Predictioncited by 32
  15. 2023Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encodingcited by 32
  16. 2023Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networkscited by 27
  17. 2023SEPT: Towards Efficient Scene Representation Learning for Motion Predictioncited by 27
  18. 2024SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous Drivingcited by 27
  19. 2022BANet: Motion Forecasting with Boundary Aware Networkcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 6.

9 papers.

  1. 2025LEGO-Motion: Learning-Enhanced Grids with Occupancy Instance Modeling for Class-Agnostic Motion Predictioncited by 6
  2. 2025Foundation Models for Trajectory Planning in Autonomous Driving: A Review of Progress and Open Challengescited by 3
  3. 2026Streaming Real-Time Trajectory Prediction Using Endpoint-Aware Modelingcited by 1
  4. 2025Duo Streamers: A Streaming Gesture Recognition Frameworkcited by 0
  5. 2026SHARP: Short-Window Streaming for Accurate and Robust Prediction in Motion Forecastingcited by 0
  6. 2026EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applicationscited by 0
  7. 2026Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bankcited by 0
  8. 2026Rethinking Training & Inference for Forecasting: Linking Winner-Take-All back to GMMscited by 0
  9. 2026LAMP: Lane-Aligned Motion Primitives for Feasible Trajectory Predictioncited by 0