Lately, Autonomous vehicles (AV) have been gaining traction globally owing to their huge
social, economic and environmental benefits. However, the rising safety apprehensions for …

Pedestrian trajectory prediction is an essential component in a wide range of AI applications
such as autonomous driving and robotics. Existing methods usually assume the training and …

Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …

Pedestrian trajectory prediction is critical in many vision tasks but challenging due to the
multimodality of the future trajectory. Most existing methods predict multimodal trajectories …

Predicting the trajectories of pedestrians in crowded conditions is an important task for
applications like autonomous navigation systems. Previous studies have tackled this …

Modeling the dynamics of people walking is a problem of long-standing interest in computer
vision. Many previous works involving pedestrian trajectory prediction define a particular set …

Understanding and forecasting future trajectories of agents are critical for behavior analysis,
robot navigation, autonomous cars, and other related applications. Previous methods mostly …

Abstract Language models have demonstrated impressive ability in context understanding
and generative performance. Inspired by the recent success of language foundation models …

Transformer Networks have established themselves as the de-facto state-of-the-art for
trajectory forecasting but there is currently no systematic study on their capability to model …

There are five types of trajectory prediction tasks: deterministic stochastic domain adaptation
momentary observation and few-shot. These associated tasks are defined by various factors …