103 citations · 131 across the 8 of their papers we have counts for
6 papers · 1 filter
LatentFormer: Multi-Agent Transformer-Based Interaction Modeling and Trajectory Prediction
Elmira Amirloo, Amir Rasouli, Peter Lakner +2
Multi-agent trajectory prediction is a fundamental problem in autonomous driving. The key challenges in prediction are accurately anticipating the behavior of surrounding agents an…
Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map
Elmira Amirloo, Mohsen Rohani, Ershad Banijamali +2
While supervised learning is widely used for perception modules in conventional autonomous driving solutions, scalability is hindered by the huge amount of data labeling needed. In…
PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3D
Amir Rasouli, Tiffany Yau, Peter Lakner +3
Predicting the behavior of road users, particularly pedestrians, is vital for safe motion planning in the context of autonomous driving systems. Traditionally, pedestrian behavior…
Bifold and Semantic Reasoning for Pedestrian Behavior Prediction
Amir Rasouli, Mohsen Rohani, Jun Luo
Pedestrian behavior prediction is one of the major challenges for intelligent driving systems. Pedestrians often exhibit complex behaviors influenced by various contextual elements…
Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction
Tiffany Yau, Saber Malekmohammadi, Amir Rasouli +3
One of the most crucial yet challenging tasks for autonomous vehicles in urban environments is predicting the future behaviour of nearby pedestrians, especially at points of crossi…
Multi-Modal Hybrid Architecture for Pedestrian Action Prediction
Amir Rasouli, Tiffany Yau, Mohsen Rohani +1
Pedestrian behavior prediction is one of the major challenges for intelligent driving systems in urban environments. Pedestrians often exhibit a wide range of behaviors and adequat…