KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long- Term Trajectory Prediction
Qiujing Lu,Weiqiao Han,Jeffrey Ling,Minfa Wang,Haoyu Chen,Balakrishnan Varadarajan,Paul Covington,Qiujing Lu,Weiqiao Han,Jeffrey Ling,Minfa Wang,Haoyu Chen,Balakrishnan Varadarajan,Paul Covington
Predicting future trajectories of road agents is a critical task for autonomous driving. Recent goal-based trajectory prediction methods, such as DenseTNT and PECNet [1], [2], 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...
