Trajectory Forecasting
72 papers with code • 4 benchmarks • 16 datasets
Trajectory forecasting is a sequential prediction task, where a forecasting model predicts future trajectories of all moving agents (humans, vehicles, etc.) in a scene, based on their past trajectories and/or the scene context.
(Illustrative figure from Social NCE: Contrastive Learning of Socially-aware Motion Representations)
Benchmarks
These leaderboards are used to track progress in Trajectory Forecasting
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Datasets
UCY
highD Dataset
inD Dataset
JAAD
TrajNet
rounD Dataset
FPL
PIE
exiD Dataset
TrajAir: A General Aviation Trajectory Dataset
Most implemented papers
From Goals, Waypoints & Paths To Long Term Human Trajectory Forecasting
harshayugirase/human-path-prediction
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ICCV 2021
Uncertainty in future trajectories stems from two sources: (a) sources that are known to the agent but unknown to the model, such as long term goals and (b)sources that are unknown to both the agent & the model, such as intent of other agents & irreducible randomness indecisions.
Real-Time Forecasting of Driver-Vehicle Dynamics on 3D Roads: a Deep-Learning Framework Leveraging Bayesian Optimisation
This represents a particularly useful problem, for instance in autonomous driving, but it does not cover a spectrum of applications in control and simulation that require information on vehicle dynamics features other than pose and orientation.
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
Khrylx/AgentFormer
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ICCV 2021
Instead, we would prefer a method that allows an agent's state at one time to directly affect another agent's state at a future time.
CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting
mipt-oulu/climat
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We show the effectiveness of our method in predicting the development of structural knee osteoarthritis changes over time.
RedMotion: Motion Prediction via Redundancy Reduction
Predicting the future motion of traffic agents is vital for self-driving vehicles to ensure their safe operation.
trajdata: A Unified Interface to Multiple Human Trajectory Datasets
nvlabs/trajdata
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NeurIPS 2023
The field of trajectory forecasting has grown significantly in recent years, partially owing to the release of numerous large-scale, real-world human trajectory datasets for autonomous vehicles (AVs) and pedestrian motion tracking.
HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
The proposed Historical Prediction Attention together with the Agent Attention and Mode Attention is further formulated as the Triple Factorized Attention module, serving as the core design of HPNet. Experiments on the Argoverse and INTERACTION datasets show that HPNet achieves state-of-the-art performance, and generates accurate and stable future trajectories.
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
coolsunxu/sophie
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CVPR 2019
Whereas, the social attention component aggregates information across the different agent interactions and extracts the most important trajectory information from the surrounding neighbors.
The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
StanfordASL/Trajectron
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ICCV 2019
Developing safe human-robot interaction systems is a necessary step towards the widespread integration of autonomous agents in society.
Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs
amiryanj/socialways
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CVPR 2019
We show through experiments on real and synthetic data that the proposed method leads to generate more diverse samples and to preserve the modes of the predictive distribution.
