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
Latest papers with no code
A Novel Benchmarking Paradigm and a Scale- and Motion-Aware Model for Egocentric Pedestrian Trajectory Prediction
To this end, we propose a novel egocentric trajectory prediction model that benefits from multimodal sources of data fused in an effective and efficient step-wise hierarchical fashion and two auxiliary tasks designed to learn more robust representation of scene dynamics.
Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks
Pedestrian motion in shared spaces is influenced by both the presence of vehicles and other pedestrians.
Pedestrian Trajectory Prediction in Pedestrian-Vehicle Mixed Environments: A Systematic Review
A practical pedestrian trajectory prediction algorithm for the use of AVs needs to consider the effect of the vehicle's interactions with the pedestrians on pedestrians' future motion behaviours.
Evaluating Pedestrian Trajectory Prediction Methods with Respect to Autonomous Driving
In this paper, we assess the state of the art in pedestrian trajectory prediction within the context of generating single trajectories, a critical aspect aligning with the requirements in autonomous systems.
Context-aware Pedestrian Trajectory Prediction with Multimodal Transformer
Quantitative results demonstrate the superiority of our proposed model over the current state-of-the-art, which consistently achieves the lowest error for 3 time horizons of 0. 5, 1. 0 and 1. 5 seconds.
Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion
In this work, we propose to separately model these two factors by implicitly deriving a flexible distribution that describes complex pedestrians' movements, whereas incorporating predictive uncertainty of individuals with explicit density functions over their future locations.
ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction
Predicting trajectories of pedestrians based on goal information in highly interactive scenes is a crucial step toward Intelligent Transportation Systems and Autonomous Driving.
Sparse Instance Conditioned Multimodal Trajectory Prediction
Specifically, SICNet learns comprehensive sparse instances, i. e., representative points of the future trajectory, through a mask generated by a long short-term memory encoder and uses the memory mechanism to store and retrieve such sparse instances.
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction
Different from previous approaches, our method can more precisely model the underlying data distribution by optimizing the exact log-likelihood of motion behaviors.
On-Board Pedestrian Trajectory Prediction Using Behavioral Features
This paper presents a novel approach to pedestrian trajectory prediction for on-board camera systems, which utilizes behavioral features of pedestrians that can be inferred from visual observations.
