Search Results for author: Sirin Haddad

Found 3 papers, 1 papers with code

Self-Growing Spatial Graph Network for Context-Aware Pedestrian Trajectory Prediction

no code implementations11 Dec 2020 Sirin Haddad, Siew-Kei Lam

To fill this gap, we propose Social Trajectory Recommender-Gated Graph Recurrent Neighborhood Network, (STR-GGRNN), which uses data-driven adaptive online neighborhood recommendation based on the contextual scene features and pedestrian visual cues.

Pedestrian Trajectory Prediction Trajectory Prediction

Graph2Kernel Grid-LSTM: A Multi-Cued Model for Pedestrian Trajectory Prediction by Learning Adaptive Neighborhoods

1 code implementation3 Jul 2020 Sirin Haddad, Siew Kei Lam

Pedestrian trajectory prediction is a prominent research track that has advanced towards modelling of crowd social and contextual interactions, with extensive usage of Long Short-Term Memory (LSTM) for temporal representation of walking trajectories.

Pedestrian Trajectory Prediction Trajectory Prediction

Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model

no code implementations13 Feb 2019 Sirin Haddad, Meiqing Wu, He Wei, Siew Kei Lam

Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation.

Autonomous Driving Collision Avoidance +3

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