View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums

Understand

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

• Previous methods mostly treat trajectory prediction as time sequence generation.
• Different from them, this work studies agents' trajectories in a "vertical" view, i.e., modeling and forecasting trajectories from the spectral domain.
• Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales.