3 papers
cs.CV2020
Probabilistic Future Prediction for Video Scene Understanding
Anthony Hu, Fergal Cotter, Nikhil Mohan +2
We present a novel deep learning architecture for probabilistic future prediction from video. We predict the future semantics, geometry and motion of complex real-world urban scene…
cs.CV2019
Urban Driving with Conditional Imitation Learning
Jeffrey Hawke, Richard Shen, Corina Gurau +8
Hand-crafting generalised decision-making rules for real-world urban autonomous driving is hard. Alternatively, learning behaviour from easy-to-collect human driving demonstrations…
cs.CV2018
Dropout Distillation for Efficiently Estimating Model Confidence
Corina Gurau, Alex Bewley, Ingmar Posner
We propose an efficient way to output better calibrated uncertainty scores from neural networks. The Distilled Dropout Network (DDN) makes standard (non-Bayesian) neural networks m…