Submitted by Nikolai Smolyanskiy.

Submission data

Full nameNVStereoNet: An Efficient Semi-Supervised Deep Neural Network Approach
DescriptionWe propose a novel semi-supervised learning approach to training a deep stereo neural network, along with a novel architecture
containing a machine-learned argmax layer and a custom, publicly available runtime that enables a smaller version of our stereo DNN to run on an
embedded GPU.
Publication titleOn the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
Publication authorsNikolai Smolyanskiy, Alexey Kamenev, Stan Birchfield
Publication venueArxiv
Publication URLhttps://arxiv.org/abs/1803.09719
Programming language(s)TensorFlow
HardwareTitan XP
Submission creation date1 Jun, 2018
Last edited1 Jun, 2018

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