深度学习,模糊图像清晰化
2019-01-11
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| EnhanceNet |
------------
This is a pre-trained reference implementation of ENet-PAT from "EnhanceNet:
Single Image Super-Resolution through Automated Texture Synthesis" for a
magnification ratio of 4.
It comes with a script which takes care of installing all necessary packages
inside a virtual environment, i.e. all installations take place inside the
folder and can be simply uninstalled by deleting the folder. Advanced users
may install the packages directly (see FAQ section).
Please note that the code has only been tested on Linux and OS/X.
If you use this code as part of a publication, please cite:
@inproceedings{enhancenet,
title={{EnhanceNet}:
Single Image Super-Resolution through Automated Texture Synthesis},
author={Sajjadi, Mehdi~S.~M. and Sch{\"o}lkopf, Be
| EnhanceNet |
------------
This is a pre-trained reference implementation of ENet-PAT from "EnhanceNet:
Single Image Super-Resolution through Automated Texture Synthesis" for a
magnification ratio of 4.
It comes with a script which takes care of installing all necessary packages
inside a virtual environment, i.e. all installations take place inside the
folder and can be simply uninstalled by deleting the folder. Advanced users
may install the packages directly (see FAQ section).
Please note that the code has only been tested on Linux and OS/X.
If you use this code as part of a publication, please cite:
@inproceedings{enhancenet,
title={{EnhanceNet}:
Single Image Super-Resolution through Automated Texture Synthesis},
author={Sajjadi, Mehdi~S.~M. and Sch{\"o}lkopf, Be
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