Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion
Dongxu Guo,Taylor Mordan,Alexandre Alahi,Dongxu Guo,Taylor Mordan,Alexandre Alahi
Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, such as when pedestrians suddenly start or stop walking. We suggest that predicting these highly non-linear transitions should form a core compon...
