G2LTraj: A Global-to-Local Generation Approach for Trajectory Prediction

arXiv:2404.19330v1 Announce Type: new
Abstract: Predicting future trajectories of traffic agents accurately holds substantial importance in various applications such as autonomous driving. Previous methods commonly infer all future steps of an agent either recursively or simultaneously. However, the recursive strategy suffers from the accumulated error, while the simultaneous strategy overlooks the constraints among future steps, resulting in kinematically infeasible predictions. To address these issues, in this paper, we propose G2LTraj, a plug-and-play global-to-local generation approach for trajectory prediction. Specifically, we …

arxiv cs.ai cs.cv global prediction trajectory type