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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
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 …
Densetnt: End-to-end trajectory prediction from dense goal sets
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 …
is challenging for autonomous driving. Recently, goal-based multi-trajectory prediction …
Transformer networks for trajectory forecasting
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 …
most recent progress has been achieved by modelling the social interaction among people …
Stgat: Modeling spatial-temporal interactions for human trajectory prediction
Human trajectory prediction is challenging and critical in various applications (eg,
autonomous vehicles and social robots). Because of the continuity and foresight of the …
autonomous vehicles and social robots). Because of the continuity and foresight of the …
Sr-lstm: State refinement for lstm towards pedestrian trajectory prediction
In crowd scenarios, reliable trajectory prediction of pedestrians requires insightful
understanding of their social behaviors. These behaviors have been well investigated by …
understanding of their social behaviors. These behaviors have been well investigated by …
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 …
Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning
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 …
complicated social dynamic systems. In many applications, effective understanding of the …
Tpnet: Trajectory proposal network for motion prediction
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 …
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
The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …
increasingly widespread testing of fully autonomous vehicles on public roads, where …