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

2020-04-09 · Ha Q. Ngo, Christoph Henke, Frank Hees

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.

📄 PDF Abstract BibTeX arXiv:2004.04787

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Prediction Trajectory Prediction

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