Multi-class Trajectory Prediction in Urban Traffic using the View-of-Delft Dataset

Critical to the safe application of autonomous vehicles is the ability to accurately predict the future motion of agents surrounding the vehicle. This is especially important - and challenging - in urban traffic, where vehicles share the road with Vulnerable Road Users (VRUs) such as pedestrians and cyclists. However, the majority of the...

Pedestrian Detection and Tracking for Mobile Robots in Human Environments

With the performance of current motion planning methods being highly dependent on the quality of the perception system, robust 3D multi-object detection and tracking are vital for autonomous driving applications. Despite all the advancements in 2D and 3D object detectors, robust tracking of pedestrians in dense scenarios is still a challenging...