Human motion trajectory prediction: A survey
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …
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 …
depending on many external factors. The topology of the scene and the interactions …
Human trajectory forecasting in crowds: A deep learning perspective
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 …
owing to its numerous real-world applications: evacuation situation analysis, deployment of …
Sophie: An attentive gan for predicting paths compliant to social and physical constraints
A Sadeghian, V Kosaraju… - Proceedings of the …, 2019 - openaccess.thecvf.com
This paper addresses the problem of path prediction for multiple interacting agents in a
scene, which is a crucial step for many autonomous platforms such as self-driving cars and …
scene, which is a crucial step for many autonomous platforms such as self-driving cars and …
A survey on long short-term memory networks for time series prediction
Recurrent neural networks and exceedingly Long short-term memory (LSTM) have been
investigated intensively in recent years due to their ability to model and predict nonlinear …
investigated intensively in recent years due to their ability to model and predict nonlinear …
Pie: A large-scale dataset and models for pedestrian intention estimation and trajectory prediction
Pedestrian behavior anticipation is a key challenge in the design of assistive and
autonomous driving systems suitable for urban environments. An intelligent system should …
autonomous driving systems suitable for urban environments. An intelligent system should …
Intention-aware vehicle trajectory prediction based on spatial-temporal dynamic attention network for internet of vehicles
X Chen, H Zhang, F Zhao, Y Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Vehicle trajectory prediction is a keystone for the application of the internet of vehicles (IoV).
With the help of deep learning and big data, it is possible to understand the between-vehicle …
With the help of deep learning and big data, it is possible to understand the between-vehicle …
Holistic LSTM for pedestrian trajectory prediction
Accurate predictions of future pedestrian trajectory could prevent a considerable number of
traffic injuries and improve pedestrian safety. It involves multiple sources of information and …
traffic injuries and improve pedestrian safety. It involves multiple sources of information and …
Recursive social behavior graph for trajectory prediction
Social interaction is an important topic in human trajectory prediction to generate plausible
paths. In this paper, we present a novel insight of group-based social interaction model to …
paths. In this paper, we present a novel insight of group-based social interaction model to …
Eigentrajectory: Low-rank descriptors for multi-modal trajectory forecasting
Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …
predicting trajectories. To address this complex nature, several attempts have been devoted …