2 papers
cs.LG2016
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.…
cs.LG2016
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…