Yuang Lu

Multiagent Trajectory Prediction With Difficulty-Guided Feature Enhancement Network

Trajectory prediction is crucial for autonomous driving, as it aims to forecast the future movements of traffic participants. Traditional methods usually perform holistic inference on the trajectories of agents, neglecting differences in prediction difficulty among agents. This letter proposes a nov