# Lornatang/ESPCN-PyTorch

<https://repo.masters-masters.com/en/repos/Lornatang/ESPCN-PyTorch>

[Home](https://repo.masters-masters.com/en) › [Lornatang](https://repo.masters-masters.com/en/owners/Lornatang) › [ESPCN-PyTorch](https://repo.masters-masters.com/en/repos/Lornatang/ESPCN-PyTorch)

Lornatang/ESPCN-PyTorch has 112 stars on GitHub. Its RepoMasters card: Prototype tier. A PyTorch implementation of ESPCN based on CVPR 2016 paper Real-Time…

| Field | Value |
| --- | --- |
| Owner | [Lornatang](https://repo.masters-masters.com/en/owners/Lornatang) |
| Stars | 112 |
| Forks | 24 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2020 |
| Topics | super-resolution, pytorch, cnn, deep-learning |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [Lornatang/ESPCN-PyTorch](https://github.com/Lornatang/ESPCN-PyTorch) |

## Repository

A PyTorch implementation of ESPCN based on CVPR 2016 paper Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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