KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long-Term Trajectory Prediction. (arXiv:2205.04624v1 [cs.CV])

Web: http://arxiv.org/abs/2205.04624

Predicting future trajectories of road agents is a critical task for
autonomous driving. Recent goal-based trajectory prediction methods, such as
DenseTNT and PECNet, have shown good performance on prediction tasks on public
datasets. However, they usually require complicated goal-selection algorithms
and optimization. In this work, we propose KEMP, a hierarchical end-to-end deep
learning framework for trajectory prediction. At the core of our framework is
keyframe-based trajectory prediction, where keyframes are representative states
that trace out the general direction of the …

arxiv cv deep hierarchical long-term model prediction