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FastPhotoStyle

Style transfer, deep learning, feature transform

Install / Use

/learn @NVIDIA/FastPhotoStyle
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

License CC BY-NC-SA 4.0 Python 2.7 Python 3.5

FastPhotoStyle

License

Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).

<img src="https://raw.githubusercontent.com/NVIDIA/FastPhotoStyle/master/teaser.png" width="800" title="Teaser results">

What's new

| Date | News | |----------|--------------| |2018-07-25| Migrate to pytorch 0.4.0. For pytorch 0.3.0 user, check out FastPhotoStyle for pytorch 0.3.0. | | | Add a tutorial showing 3 ways of using the FastPhotoStyle algorithm.| |2018-07-10| Our paper is accepted by the ECCV 2018 conference!!! |

About

Given a content photo and a style photo, the code can transfer the style of the style photo to the content photo. The details of the algorithm behind the code is documented in our arxiv paper. Please cite the paper if this code repository is used in your publications.

A Closed-form Solution to Photorealistic Image Stylization <br> Yijun Li (UC Merced), Ming-Yu Liu (NVIDIA), Xueting Li (UC Merced), Ming-Hsuan Yang (NVIDIA, UC Merced), Jan Kautz (NVIDIA) <br> European Conference on Computer Vision (ECCV), 2018 <br>

Tutorial

Please check out the tutorial.

Related Skills

View on GitHub
GitHub Stars11.2k
CategoryEducation
Updated3d ago
Forks1.2k

Languages

Python

Security Score

80/100

Audited on Mar 22, 2026

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