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
Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction
We employ MESRNN for pedestrian trajectory prediction, utilizing these meta-path based features to capture the relationships between the trajectories of pedestrians at different points in time and space.
Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation
abduallahmohamed/social-implicit
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AMD is a metric that quantifies how close the whole generated samples are to the ground truth.
SocialVAE: Human Trajectory Prediction using Timewise Latents
Predicting pedestrian movement is critical for human behavior analysis and also for safe and efficient human-agent interactions.
Non-Probability Sampling Network for Stochastic Human Trajectory Prediction
Capturing multimodal natures is essential for stochastic pedestrian trajectory prediction, to infer a finite set of future trajectories.
Social Interpretable Tree for Pedestrian Trajectory Prediction
lssiair/sit
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Understanding the multiple socially-acceptable future behaviors is an essential task for many vision applications.
Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction
Pedestrian trajectory prediction is an essential and challenging task for a variety of real-life applications such as autonomous driving and robotic motion planning.
T2FPV: Dataset and Method for Correcting First-Person View Errors in Pedestrian Trajectory Prediction
cmubig/t2fpv
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To support first-person view trajectory prediction research, we present T2FPV, a method for constructing high-fidelity first-person view (FPV) datasets given a real-world, top-down trajectory dataset; we showcase our approach on the ETH/UCY pedestrian dataset to generate the egocentric visual data of all interacting pedestrians, creating the T2FPV-ETH dataset.
Pishgu: Universal Path Prediction Network Architecture for Real-time Cyber-physical Edge Systems
These real-world CPS applications need a robust, lightweight path prediction that can provide a universal network architecture for multiple subjects (e. g., pedestrians and vehicles) from different perspectives.
G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction System
aryan-garg/pecnet-pedestrian-trajectory-prediction
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Navigating dynamic physical environments without obstructing or damaging human assets is of quintessential importance for social robots.
Trajectory Unified Transformer for Pedestrian Trajectory Prediction
Pedestrian trajectory prediction is an essentially connecting link to understanding human behavior.
