626 citations · 1.2k across the 12 of their papers we have counts for
3 papers · 1 filter
Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks
Julie Dequaire, Dushyant Rao, Peter Ondruska +2
This paper presents an end-to-end approach for tracking static and dynamic objects for an autonomous vehicle driving through crowded urban environments. Unlike traditional approach…
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks
Peter Ondruska, Julie Dequaire, Dominic Zeng Wang +1
In this work we present a novel end-to-end framework for tracking and classifying a robot's surroundings in complex, dynamic and only partially observable real-world environments.…
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Peter Ondruska, Ingmar Posner
This paper presents to the best of our knowledge the first end-to-end object tracking approach which directly maps from raw sensor input to object tracks in sensor space without re…