mlsanityData to 7 Oct 2026

Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

arXiv 2101.02385 ↗First posted 7 Jan 2021cs.CV cs.LG cs.ROcited by 6

Not on the map. Why?

Abstract (arXiv)

In this paper, we address the important problem in self-driving of forecasting multi-pedestrian motion and their shared scene occupancy map, critical for safe navigation. Our contributions are two-fold. First, we advocate for predicting both the individual motions as well as the scene occupancy map in order to effectively deal with missing detections caused by postprocessing, e.g., confidence thresholding and non-maximum suppression. Second, we propose a Scene-Actor Graph Neural Network (SA-GNN) which preserves the relative spatial information of pedestrians via 2D convolution, and captures the interactions among pedestrians within the same scene, including those that have not been detected, via message passing. On two large-scale real-world datasets, nuScenes and ATG4D, we showcase that our scene-occupancy predictions are more accurate and better calibrated than those from state-of-the-art motion forecasting methods, while also matching their performance in pedestrian motion forecasting metrics.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 52 of its 66 references that are in the map. First posted on arXiv 7 Jan 2021.

Builds on

52 of 66 references.

References · 52

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2017Mask R-CNNcited by 7,259
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2017On Calibration of Modern Neural Networkscited by 4,860
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  6. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  7. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  8. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  9. 2018Group Normalizationcited by 1,514
  10. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  11. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  12. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 939
38 more
  1. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 721
  2. 2018Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networkscited by 687
  3. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  4. 2016Training Region-based Object Detectors with Online Hard Example Miningcited by 577
  5. 2019PointPainting: Sequential Fusion for 3D Object Detectioncited by 449
  6. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  7. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
  8. 2019PIXOR: Real-time 3D Object Detection from Point Cloudscited by 358
  9. 2019Class-balanced Grouping and Sampling for Point Cloud 3D Object Detectioncited by 350
  10. 2018Neural Relational Inference for Interacting Systemscited by 339
  11. 2017Joint 3D Proposal Generation and Object Detection from View Aggregationcited by 325
  12. 2020Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Predictioncited by 324
  13. 2018An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solutioncited by 302
  14. 2018SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraintscited by 296
  15. 2019STD: Sparse-to-Dense 3D Object Detector for Point Cloudcited by 282
  16. 2020Deep Continuous Fusion for Multi-Sensor 3D Object Detectioncited by 263
  17. 2019Human Motion Trajectory Prediction: A Surveycited by 231
  18. 2019Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networkscited by 228
  19. 2020Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Netcited by 228
  20. 2020Multi-Task Multi-Sensor Fusion for 3D Object Detectioncited by 203
  21. 2019Multiple Futures Predictioncited by 178
  22. 2019End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Cloudscited by 171
  23. 2020Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representationscited by 150
  24. 2020PnPNet: End-to-End Perception and Prediction with Tracking in the Loopcited by 143
  25. 2020Implicit Latent Variable Model for Scene-Consistent Motion Forecastingcited by 116
  26. 2015Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Imagescited by 111
  27. 2019Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Datacited by 104
  28. 2020HDNET: Exploiting HD Maps for 3D Object Detectioncited by 78
  29. 2016Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networkscited by 72
  30. 2016Online Multi-Target Tracking Using Recurrent Neural Networkscited by 59
  31. 20163D Fully Convolutional Network for Vehicle Detection in Point Cloudcited by 57
  32. 2018Inference in Probabilistic Graphical Models by Graph Neural Networkscited by 38
  33. 2017Situation Recognition with Graph Neural Networkscited by 34
  34. 2019Discrete Residual Flow for Probabilistic Pedestrian Behavior Predictioncited by 34
  35. 2017Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labelingcited by 30
  36. 2016Convolutional Gated Recurrent Networks for Video Segmentationcited by 27
  37. 2020The Importance of Prior Knowledge in Precise Multimodal Predictioncited by 25
  38. 2019StarNet: Pedestrian Trajectory Prediction using Deep Neural Network in Star Topologycited by 17

50 most cited of 52 All 52 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 3; 2024: 0; 2025: 0; 2026: 1.

6 papers.

  1. 2022Behavioral Intention Prediction in Driving Scenes: A Surveycited by 30
  2. 2023Implicit Occupancy Flow Fields for Perception and Prediction in Self-Drivingcited by 30
  3. 2021ObserveNet Control: A Vision-Dynamics Learning Approach to Predictive Control in Autonomous Vehiclescited by 0
  4. 2023Comparison of Pedestrian Prediction Models from Trajectory and Appearance Data for Autonomous Drivingcited by 0
  5. 2023Semantic and Articulated Pedestrian Sensing Onboard a Moving Vehiclecited by 0
  6. 2026TSCA-Net: Temporal-Spatial Clique Attention for Interpretable Multimodal Pedestrian Trajectory Predictioncited by 0