With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …

There is a dilemma regarding the accuracy and reality of vehicle trajectory prediction.
Balancing and predicting the effective trajectory is a topic of debate in autonomous driving …

Vehicle trajectory prediction has increasingly relied on data-driven solutions, but their ability
to scale to different data domains and the impact of larger dataset sizes on their …

Learning socially-aware motion representations is at the core of recent advances in multi-
agent problems, such as human motion forecasting and robot navigation in crowds. Despite …

The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …

Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the
industry and research communities have acknowledged the need for such a pillar by …

Human trajectory forecasting is a key component of autonomous vehicles, social-aware
robots and advanced video-surveillance applications. This challenging task typically …

Learning behavioral patterns from observational data has been a de-facto approach to
motion forecasting. Yet, the current paradigm suffers from two shortcomings: brittle under …

Vehicle trajectory prediction tasks have been commonly tackled from two distinct
perspectives: either with knowledge-driven methods or more recently with data-driven ones …