An End-to-End Learning Approach for Trajectory Prediction in Pedestrian Zones

04/09/2020
by   Ha Q. Ngo, et al.
0

This paper aims to explore the problem of trajectory prediction in heterogeneous pedestrian zones, where social dynamics representation is a big challenge. Proposed is an end-to-end learning framework for prediction accuracy improvement based on an attention mechanism to learn social interaction from multi-factor inputs.

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