Perception and prediction are two separate modules in the existing autonomous driving
systems. They interact with each other via hand-picked features such as agent bounding …

Existing trajectory prediction methods for autonomous driving typically rely on one-stage
trajectory prediction models which condition future trajectories on observed trajectories …

Trajectory prediction has been a crucial task in building a reliable autonomous driving
system by anticipating possible dangers. One key issue is to generate consistent trajectory …

Predicting the trajectory of other road users, especially vulnerable road users (VRUs), is an
important aspect of safety and planning efficiency for autonomous vehicles. With recent …

Trajectory prediction plays a crucial role in bridging the gap between perception and
planning in autonomous driving systems. However, most existing methods perform motion …

Trajectory prediction is a challenging problem that requires considering interactions among
multiple actors and the surrounding environment. While data-driven approaches have been …

Accurate prediction of the future motion of surrounding vehicles is crucial for ensuring the
safety of motion planning in autonomous vehicles. However, it is challenging to perform …

Predicting the future trajectories of dynamic traffic actors is a cornerstone task in
autonomous driving. Though existing notable efforts have resulted in impressive …

Recently, anchor-based trajectory prediction methods have shown promising performance,
which directly selects a final set of anchors as future intents in the spatio-temporal coupled …

Predicting temporally consistent road users' trajectories in a multi-agent setting is a
challenging task due to unknown characteristics of agents and their varying intentions …