Pedestrian Trajectory Prediction
37 papers with code • 1 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Pedestrian Trajectory Prediction
| Trend | Dataset | Best Model | Paper | Code | Compare |
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JAAD
PIE
Euro-PVI
Most implemented papers
Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras
olly-styles/Multi-Camera-Trajectory-Forecasting
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To facilitate research in this new area, we release the Warwick-NTU Multi-camera Forecasting Database (WNMF), a unique dataset of multi-camera pedestrian trajectories from a network of 15 synchronized cameras.
Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction
In this paper, we present STAR, a Spatio-Temporal grAph tRansformer framework, which tackles trajectory prediction by only attention mechanisms.
Long-term Pedestrian Trajectory Prediction using Mutable Intention Filter and Warp LSTM
Trajectory prediction is one of the key capabilities for robots to safely navigate and interact with pedestrians.
Graph2Kernel Grid-LSTM: A Multi-Cued Model for Pedestrian Trajectory Prediction by Learning Adaptive Neighborhoods
serenetech90/multimodaltraj_2
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Pedestrian trajectory prediction is a prominent research track that has advanced towards modelling of crowd social and contextual interactions, with extensive usage of Long Short-Term Memory (LSTM) for temporal representation of walking trajectories.
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation
umautobots/bidireaction-trajectory-prediction
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BiTraP estimates the goal (end-point) of trajectories and introduces a novel bi-directional decoder to improve longer-term trajectory prediction accuracy.
Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision
Predicting human motion behavior in a crowd is important for many applications, ranging from the natural navigation of autonomous vehicles to intelligent security systems of video surveillance.
Asymmetrical Bi-RNN for pedestrian trajectory encoding
JosephGesnouin/Asymmetrical-Bi-RNNs-to-encode-pedestrian-trajectories
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Pedestrian motion behavior involves a combination of individual goals and social interactions with other agents.
Learning Sparse Interaction Graphs of Partially Detected Pedestrians for Trajectory Prediction
tedhuang96/gst
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Multi-pedestrian trajectory prediction is an indispensable element of autonomous systems that safely interact with crowds in unstructured environments.
Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction
yutasq/multi-class-social-stgcnn
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This is because they ignore the impact of the implicit correlations between different types of road users on the trajectory to be predicted - for example, a nearby pedestrian has a different level of influence from a nearby car.
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction
Pedestrian trajectory prediction is challenging due to its uncertain and multimodal nature.
