Autonomous vehicle navigation in shared pedestrian environments requires the ability to
predict future crowd motion both accurately and with minimal delay. Understanding the …

Pedestrian trajectory prediction is of great importance for downstream tasks, such as
autonomous driving and mobile robot navigation. Realistic models of the social interactions …

Understanding and predicting the intention of pedestrians is essential to enable
autonomous vehicles and mobile robots to navigate crowds. This problem becomes …

To enable safe and efficient navigations through the urban environment, autonomous
vehicles need to anticipate the future motions of the walking pedestrians who might collide …

Pedestrian trajectory prediction is a critical yet challenging task especially for crowded
scenes. We suggest that introducing an attention mechanism to infer the importance of …

Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving
and robot navigation. However, predicting a pedestrian's trajectory in crowded environments …

Urban environments pose a significant challenge for autonomous vehicles (AVs) as they
must safely navigate while in close proximity to many pedestrians. It is crucial for the AV to …

Trajectory prediction, also known as trajectory forecasting, of interacting agents in dynamic
scenes is a critical problem for many applications, including robotic systems and …

Pedestrian trajectory prediction is a crucial task for many domains, such as self-driving,
navigation robots and video surveillance. The performance of trajectory prediction can be …

Pedestrian trajectory prediction is crucial in many practical applications due to the diversity
of pedestrian movements, such as social interactions and individual motion behaviors. With …