Important resources if you are working with Neural Style Transfer or Deep Photo Style Transfer

The Starry Night by Vincent van Gogh

Neural style transfer and deep photo style transfer are interesting fields of deep learning. Their popularity has grown to an another level. Apps like Prisma and Deepart.io accelerated the popularity. If you are working with neural style transfer or deep photo style transfer these are some very important resources(papers, implementations and tutorials) to help you out.

Research Papers

• A Neural Algorithm of Artistic Style

[1508.06576] A Neural Algorithm of Artistic Style

• Neural Style Transfer — A Review

[1705.04058] Neural Style Transfer: A Review

• Deep Photo Style Transfer

[1703.07511] Deep Photo Style Transfer

• Controlling Perceptual Factors in Neural Style Transfer

[1611.07865] Controlling Perceptual Factors in Neural Style Transfer

• Instance Normalization: The Missing Ingredient for Fast Stylization

[1607.08022] Instance Normalization: The Missing Ingredient for Fast Stylization

Implementations

• Torch implementation of Neural Style Transfer

jcjohnson/neural-style

• Tensorflow Implementation of Neural Style Transfer

anishathalye/neural-style

An AI That Can Mimic Any Artist · cat /var/log/life

cysmith/neural-style-tf

log0/neural-style-painting

woodrush/neural-art-tf

• Torch implementation of Deep Photo Style Transfer

luanfujun/deep-photo-styletransfer

• Tensorflow implementation of Deep Photo Style Transfer

LouieYang/deep-photo-styletransfer-tf

• Tensorflow implementation of Fast Style Transfer

lengstrom/fast-style-transfer

• Torch7(Lua) implementation of Neural Style Transfer

kaishengtai/neuralart

• Keras implementation of Neural Style Transfer

fchollet/keras

titu1994/Neural-Style-Transfer

kevinzakka/style_transfer

• Theano+Keras implementation of style transfer algorithms

jayanthkoushik/neural-style

• DeepPy implementation of Neural Artisitic Style

andersbll/neural_artistic_style

• pyCaffe implementation of Neural Artistic Style

fzliu/style-transfer

• Caffe implementation of Neural Style Transfer

ftokarev/caffe-neural-style

• MXNet implementation of Neural Style Transfer

apache/incubator-mxnet

• Chainer implementation of Neural Style Transfer

dsanno/chainer-neural-style

• MXNet pre-trained model for Neural Style Transfer

https://github.com/dmlc/web-data/raw/master/mxnet/art/model.zip

Tutorials

Convolutional neural networks for artistic style transfer

How do these "neural network style transfer" tools work?

Neural Transfer with PyTorch - PyTorch Tutorials 0.2.0_2 documentation

Painting like Van Gogh with Convolutional Neural Networks

End to End Neural Art with Generative Models

TensorFlow Implementation of "A Neural Algorithm of Artistic Style"

Installing Neural-Style On A Mac

Gruff's Tech Tips

Video Tutorials

Articles

Deep neural networks can now transfer the style of one photo onto another

Deep neural networks can now transfer the style of one photo onto another

Create Your Own "Neural Paintings" with DeepStyle & Ubuntu

Experiments with style transfer

Neural Style Explained

Neural Style Transfer - New Media New Technology 2017

Extreme Style Machines: Using Random Neural Networks to Generate Textures

Add or Delete a Painter's Style Using Neural Algorithms

Companies using Neural Style Transfer/Deep Photo Style Transfer

deepart.io - become a digital artist

Neural Style | Neural Algorithm of Artistic Style

Pikazo - Make Anything Art

Instapainting

NeuralStyler

Docker implementation of jcjohnson neural-style code

https://hub.docker.com/r/ffedoroff/neural-style/

Audio Texture Synthesis and style transfer

Audio texture synthesis and style transfer

DmitryUlyanov/neural-style-audio-tf

DmitryUlyanov/neural-style-audio-torch

vadim-v-lebedev/audio_style_tranfer

Reddit Thread

Mathematica(StackExchange)

How to implement neural style transfer?

Thank you for reading.

If you want to get into contact, you can reach out to me at ahikailash1@gmail.com

About Me:

I am a Co-Founder of MateLabs, where we have built Mateverse, an ML Platform which enables everyone to easily build and train Machine Learning Models, without writing a single line of code.

Note: Recently, I published a book on GANs titled “Generative Adversarial Networks Projects”, in which I covered most of the widely popular GAN architectures and their implementations. DCGAN, StackGAN, CycleGAN, Pix2pix, Age-cGAN, and 3D-GAN have been covered in details at the implementation level. Each architecture has a chapter dedicated to it. I have explained these networks in a very simple and descriptive language using Keras framework with Tensorflow backend. If you are working on GANs or planning to use GANs, give it a read and share your valuable feedback with me at ahikailash1@gmail.com

Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow…

You can grab a copy of the book from http://www.amazon.com/Generative-Adversarial-Networks-Projects-next-generation/dp/1789136679https://www.amazon.in/Generative-Adversarial-Networks-Projects-next-generation/dp/1789136679?fbclid=IwAR0X2pDk4CTxn5GqWmBbKIgiB38WmFX-sqCpBNI8k9Z8I-KCQ7VWRpJXm7I https://www.packtpub.com/big-data-and-business-intelligence/generative-adversarial-networks-projects?fbclid=IwAR2OtU21faMFPM4suH_HJmy_DRQxOVwJZB0kz3ZiSbFb_MW7INYCqqV7U0c