103 citations · 155 across the 18 of their papers we have counts for
7 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…
PURE: Passive mUlti-peRson idEntification via Deep Footstep Separation and Recognition
Chao Cai, Ruinan Jin, Peng Wang +3
Recently, \textit{passive behavioral biometrics} (e.g., gesture or footstep) have become promising complements to conventional user identification methods (e.g., face or fingerprin…
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…