2 citations · 3 across the 5 of their papers we have counts for
Showing 2017Show all
2 papers · 1 filter
cs.LG2017
Generative learning for deep networks
Boris Flach, Alexander Shekhovtsov, Ondrej Fikar
Learning, taking into account full distribution of the data, referred to as generative, is not feasible with deep neural networks (DNNs) because they model only the conditional dis…
cs.CV2017
Scalable Full Flow with Learned Binary Descriptors
Gottfried Munda, Alexander Shekhovtsov, Patrick Knöbelreiter +1
We propose a method for large displacement optical flow in which local matching costs are learned by a convolutional neural network (CNN) and a smoothness prior is imposed by a con…