mlsanityData to 7 Oct 2026

RNN-based Pedestrian Crossing Prediction using Activity and Pose-related Features

arXiv 2008.11647 ↗First posted 26 Aug 2020cs.CV cs.LGcited by 21

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Abstract (arXiv)

Pedestrian crossing prediction is a crucial task for autonomous driving. Numerous studies show that an early estimation of the pedestrian's intention can decrease or even avoid a high percentage of accidents. In this paper, different variations of a deep learning system are proposed to attempt to solve this problem. The proposed models are composed of two parts: a CNN-based feature extractor and an RNN module. All the models were trained and tested on the JAAD dataset. The results obtained indicate that the choice of the features extraction method, the inclusion of additional variables such as pedestrian gaze direction and discrete orientation, and the chosen RNN type have a significant impact on the final performance.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 4; 2023: 1; 2024: 3; 2025: 6; 2026: 4.

21 papers.

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  1. 2021Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attentioncited by 48
  2. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  3. 2021IntFormer: Predicting pedestrian intention with the aid of the Transformer architecturecited by 13
  4. 2024PIP-Net: Pedestrian Intention Prediction in the Wildcited by 11
  5. 2022Deep Virtual-to-Real Distillation for Pedestrian Crossing Predictioncited by 10
  6. 2022Testing predictive automated driving systems: lessons learned and future recommendationscited by 6
  7. 2022On-Board Pedestrian Trajectory Prediction Using Behavioral Featurescited by 5
  8. 2022WatchPed: Pedestrian Crossing Intention Prediction Using Embedded Sensors of Smartwatchcited by 3
  9. 2024Context-aware Multi-task Learning for Pedestrian Intent and Trajectory Predictioncited by 3
  10. 2025SGNetPose+: Stepwise Goal-Driven Networks with Pose Information for Trajectory Prediction in Autonomous Drivingcited by 2
  11. 2025TrajFusionNet: Pedestrian Crossing Intention Prediction via Fusion of Sequential and Visual Trajectory Representationscited by 2
  12. 2021Single Shot Multitask Pedestrian Detection and Behavior Predictioncited by 1
9 more
  1. 2024Feature Importance in Pedestrian Intention Prediction: A Context-Aware Reviewcited by 1
  2. 2025Pedestrian Intention and Trajectory Prediction in Unstructured Traffic Using IDD-PeDcited by 1
  3. 2025Occlusion-Aware Diffusion Model for Pedestrian Intention Predictioncited by 1
  4. 2023Semantic and Articulated Pedestrian Sensing Onboard a Moving Vehiclecited by 0
  5. 2025Temporal-contextual Event Learning for Pedestrian Crossing Intent Predictioncited by 0
  6. 2026Context-free Self-Conditioned GAN for Trajectory Forecastingcited by 0
  7. 2026ARCANE-PedSynth: Synthetic Multi-Pedestrian Datasets with Behavioural Crossing Annotationscited by 0
  8. 2026Unified Vision-Centric Pedestrian Crossing Action Prediction via Adaptive Patch Projection and Proactive Spatial Rectificationcited by 0
  9. 2026MTF-Net: Multi-Modal Temporal Feature Fusion Network for Pedestrian Intention Predictioncited by 0