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Michele Covell

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Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression

Feb 09, 2021
A. Murat Tekalp, Michele Covell, Radu Timofte, Chao Dong

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Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference

Jun 11, 2019
Michele Covell, David Marwood, Shumeet Baluja, Nick Johnston

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Neural Image Decompression: Learning to Render Better Image Previews

Dec 06, 2018
Shumeet Baluja, Dave Marwood, Nick Johnston, Michele Covell

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No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference

Sep 28, 2018
Shumeet Baluja, David Marwood, Michele Covell, Nick Johnston

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Representing Images in 200 Bytes: Compression via Triangulation

Sep 20, 2018
David Marwood, Pascal Massimino, Michele Covell, Shumeet Baluja

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Image-Dependent Local Entropy Models for Learned Image Compression

May 31, 2018
David Minnen, George Toderici, Saurabh Singh, Sung Jin Hwang, Michele Covell

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Spatially adaptive image compression using a tiled deep network

Feb 07, 2018
David Minnen, George Toderici, Michele Covell, Troy Chinen, Nick Johnston, Joel Shor, Sung Jin Hwang, Damien Vincent, Saurabh Singh

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Full Resolution Image Compression with Recurrent Neural Networks

Jul 07, 2017
George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell

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Target-Quality Image Compression with Recurrent, Convolutional Neural Networks

May 18, 2017
Michele Covell, Nick Johnston, David Minnen, Sung Jin Hwang, Joel Shor, Saurabh Singh, Damien Vincent, George Toderici

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Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

Mar 29, 2017
Nick Johnston, Damien Vincent, David Minnen, Michele Covell, Saurabh Singh, Troy Chinen, Sung Jin Hwang, Joel Shor, George Toderici

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