Human motion trajectory prediction: A survey

A Rudenko, L Palmieri, M Herman… - … Journal of Robotics …, 2020‏ - journals.sagepub.com
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches

R Korbmacher, A Tordeux - IEEE Transactions on Intelligent …, 2022‏ - ieeexplore.ieee.org
In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task
depending on many external factors. The topology of the scene and the interactions …

Densetnt: End-to-end trajectory prediction from dense goal sets

J Gu, C Sun, H Zhao - Proceedings of the IEEE/CVF …, 2021‏ - openaccess.thecvf.com
Due to the stochasticity of human behaviors, predicting the future trajectories of road agents
is challenging for autonomous driving. Recently, goal-based multi-trajectory prediction …

Transformer networks for trajectory forecasting

F Giuliari, I Hasan, M Cristani… - 2020 25th international …, 2021‏ - ieeexplore.ieee.org
Most recent successes on forecasting the people motion are based on LSTM models and all
most recent progress has been achieved by modelling the social interaction among people …

Stgat: Modeling spatial-temporal interactions for human trajectory prediction

Y Huang, H Bi, Z Li, T Mao… - Proceedings of the IEEE …, 2019‏ - openaccess.thecvf.com
Human trajectory prediction is challenging and critical in various applications (eg,
autonomous vehicles and social robots). Because of the continuity and foresight of the …

Sr-lstm: State refinement for lstm towards pedestrian trajectory prediction

P Zhang, W Ouyang, P Zhang… - Proceedings of the …, 2019‏ - openaccess.thecvf.com
In crowd scenarios, reliable trajectory prediction of pedestrians requires insightful
understanding of their social behaviors. These behaviors have been well investigated by …

Human trajectory forecasting in crowds: A deep learning perspective

P Kothari, S Kreiss, A Alahi - IEEE Transactions on Intelligent …, 2021‏ - ieeexplore.ieee.org
Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …

Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning

J Li, F Yang, M Tomizuka… - Advances in neural …, 2020‏ - proceedings.neurips.cc
Multi-agent interacting systems are prevalent in the world, from purely physical systems to
complicated social dynamic systems. In many applications, effective understanding of the …

Tpnet: Trajectory proposal network for motion prediction

L Fang, Q Jiang, J Shi, B Zhou - Proceedings of the IEEE …, 2020‏ - openaccess.thecvf.com
Making accurate motion prediction of the surrounding traffic agents such as pedestrians,
vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …

State estimation and motion prediction of vehicles and vulnerable road users for cooperative autonomous driving: A survey

P Ghorai, A Eskandarian, YK Kim… - IEEE transactions on …, 2022‏ - ieeexplore.ieee.org
The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …