Human behavior has the nature of indeterminacy, which requires the pedestrian trajectory
prediction system to model the multi-modality of future motion states. Unlike existing …

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 …

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 …

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 …

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

State-of-the-art AI models largely lack an understanding of the cause-effect relationship that
governs human understanding of the real world. Consequently, these models do not …

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

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

For safe motion planning in real-world autonomous vehicles require behavior prediction
models that are reliable and robust to distribution shifts. The recent studies suggest that the …

Trajectory prediction is a crucial undertaking in understanding entity movement or human
behavior from observed sequences. However, current methods often assume that the …