Style Transfer

Neural Art

A Neural Algorithm of Artistic Style

• arxiv: http://arxiv.org/abs/1508.06576
• gitxiv: http://gitxiv.com/posts/jG46ukGod8R7Rdtud/a-neural-algorithm-of-artistic-style
• github: https://github.com/kaishengtai/neuralart
• github: https://github.com/jcjohnson/neural-style
• github: https://github.com/andersbll/neural_artistic_style
• ipn: http://nbviewer.ipython.org/github/Lasagne/Recipes/blob/master/examples/styletransfer/Art%20Style%20Transfer.ipynb
• github: https://github.com/mbartoli/neural-animation
• github: https://github.com/memisevic/artify
• github: https://github.com/mattya/chainer-gogh
• github(TensorFlow): https://github.com/anishathalye/neural-style
• github: https://github.com/woodrush/neural-art-tf
• github: https://github.com/dmlc/mxnet/tree/master/example/neural-style
• demo: http://deepart.io/
• github: https://github.com/Teaonly/easyStyle
• github: https://github.com/ckmarkoh/neuralart_tensorflow
• github: https://github.com/fzliu/style-transfer
• github: https://github.com/titu1994/Neural-Style-Transfer
• github: https://github.com/saikatbsk/Vincent-AI-Artist
• github: https://github.com/zhaw/neural_style

Image Style Transfer Using Convolutional Neural Networks

• paper: www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf

Artificial Startup Style: Neural art about startup fashion

• blog: https://medium.com/data-engineering/artificial-startup-style-437f6090b1f7#.8u06gq42e

From Pixels to Paragraphs: How artistic experiments with deep learning guard us from hype

• blog: https://medium.com/@genekogan/from-pixels-to-paragraphs-eb2763da0e9b#.er3djn9z9

Experiments with style transfer

• website: http://mtyka.github.io/code/2015/10/02/experiments-with-style-transfer.html

Style Transfer for Headshot Portraits (SIGGRAPH 2014)

• project: https://people.csail.mit.edu/yichangshih/portrait_web/

Teaching recurrent Neural Networks about Monet

• blog: http://blog.manugarri.com/teaching-recurrent-neural-networks-about-monet/
• github: https://github.com/manugarri/keras_monet

Content Aware Neural Style Transfer

• arxiv: http://arxiv.org/abs/1601.04568

Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

• arxiv: http://arxiv.org/abs/1601.04589
• github: https://github.com/chuanli11/CNNMRF

Stylenet: Neural Network with Style Synthesis

• github: https://github.com/machrisaa/stylenet

Ostagram

• intro: This program presents web-service for algorithm combining the content of one image with the style of another image using convolutional neural networks
• github: https://github.com/SergeyMorugin/ostagram

Exploring the Neural Algorithm of Artistic Style

• intro: A short class project report
• arxiv: http://arxiv.org/abs/1602.07188

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

• intro: Justin Johnson, Alexandre Alahi, Li Fei-Fei. ECCV 2016
• arxiv: http://arxiv.org/abs/1603.08155
• github: https://github.com/jcjohnson/fast-neural-style
• github: https://github.com/yusuketomoto/chainer-fast-neuralstyle
• github: https://github.com/awentzonline/keras-rtst
• github(Keras): https://github.com/titu1994/Fast-Neural-Style
• gtihub(Tensorflow): [https://github.com/junrushao1994/fast-neural-style.tf] (https://github.com/junrushao1994/fast-neural-style.tf)
• github(PyTorch): https://github.com/bengxy/FastNeuralStyle

Image transformation networks with fancy loss functions

• intro: Fast neural style in tensorflow based on http://arxiv.org/abs/1603.08155
• blog: http://olavnymoen.com/2016/07/07/image-transformation-network
• github: https://github.com/OlavHN/fast-neural-style

Improving the Neural Algorithm of Artistic Style

• arxiv: http://arxiv.org/abs/1605.04603

CubistMirror: an openframeworks app which repeatedly applies real-time style transfer on a webcam

• github: https://github.com/genekogan/CubistMirror

Transfer Style But Not Color

• blog: http://blog.deepart.io/2016/06/04/color-independent-style-transfer/
• github: https://github.com/pavelgonchar/color-independent-style-transfer

neural-art-mini: Lightweight version of mxnet neural art implementation

• intro: Lightweight version of mxnet neural art implementation using ~4.8M SqueezeNet model. Compressed model is less than 500KB
• github: https://github.com/pavelgonchar/neural-art-mini

Preserving Color in Neural Artistic Style Transfer

• arxiv: http://arxiv.org/abs/1606.05897

End to End Neural Art with Generative Models

• blog: http://dmlc.ml/mxnet/2016/06/20/end-to-end-neural-style.html
• github: https://github.com/dmlc/mxnet/tree/master/example/neural-style

Neural Style Explained

• blog: http://kvfrans.com/neural-style-explained/
• github: https://github.com/kvfrans/neural-style

Texture Networks: Feed-forward Synthesis of Textures and Stylized Images

• intro: IMCL 2016
• arxiv: http://arxiv.org/abs/1603.03417
• github: https://github.com/DmitryUlyanov/texture_nets
• notes: https://blog.acolyer.org/2016/09/23/texture-networks-feed-forward-synthesis-of-textures-and-stylized-images/
• github: https://github.com/tgyg-jegli/tf_texture_net

Learning Typographic Style

• arxiv: https://arxiv.org/abs/1603.04000

Instance Normalization: The Missing Ingredient for Fast Stylization

• arxiv: http://arxiv.org/abs/1607.08022

Painting style transfer for head portraits using convolutional neural networks

• paper: http://dl.acm.org/citation.cfm?id=2925968
• sci-hub: http://dl.acm.org.sci-hub.cc/citation.cfm?doid=2897824.2925968

Style-Transfer via Texture-Synthesis

• arxiv: http://arxiv.org/abs/1609.03057

neural-style-tf: TensorFlow implementation of Neural Style

• github: https://github.com/cysmith/neural-style-tf

Deep Convolutional Networks as Models of Generalization and Blending Within Visual Creativity

• intro: In Proceedings of the 7th International Conference on Computational Creativity. Palo Alto: Association for the Advancement of Artificial Intelligence (AAAI) Press (2016)
• arxiv: https://arxiv.org/abs/1610.02478

A Learned Representation For Artistic Style

• intro: Google Brain
• arxiv: https://arxiv.org/abs/1610.07629
• blog: https://research.googleblog.com/2016/10/supercharging-style-transfer.html
• github: https://github.com/tensorflow/magenta/tree/master/magenta/models/image_stylization
• github(Tensorflow): https://github.com/Heumi/Fast_Multi_Style_Transfer-tf

How to Fake It As an Artist with Docker, AWS and Deep Learning

• blog: https://medium.com/@lherrera/how-to-fake-it-as-an-artist-with-docker-aws-and-deep-learning-6d42f4acd890#.eq9gcgkzh

Multistyle Pastiche Generator

• blog: https://magenta.tensorflow.org/2016/11/01/multistyle-pastiche-generator/

Fast Style Transfer in TensorFlow

• intro: Video Stylization, Image Stylization
• github: https://github.com/lengstrom/fast-style-transfer

Neural Style Transfer For Chinese Fonts

• github: https://github.com/kaonashi-tyc/Rewrite

Neural Style Representations and the Large-Scale Classification of Artistic Style

• arxiv: https://arxiv.org/abs/1611.05368

Controlling Perceptual Factors in Neural Style Transfer

• intro: University of Tubingen & Adobe Research
• arxiv: https://arxiv.org/abs/1611.07865

Awesome Typography: Statistics-Based Text Effects Transfer

• arxiv: https://arxiv.org/abs/1611.09026

Fast Patch-based Style Transfer of Arbitrary Style

• arxiv: https://arxiv.org/abs/1612.04337
• github: https://github.com/rtqichen/style-swap

Demystifying Neural Style Transfer

• intro: IJCAI 2017
• intro: Peking University & TuSimple
• arxiv: https://arxiv.org/abs/1701.01036
• github: https://github.com/lyttonhao/Neural-Style-MMD

Son of Zorn’s Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentation

• arxiv: https://arxiv.org/abs/1701.02357

Bringing Impressionism to Life with Neural Style Transfer in Come Swim

• intro: a case study of how Neural Style Transfer can be used in a movie production context
• keywords: Kristen Stewart !
• arxiv: https://arxiv.org/abs/1701.04928

Pytorch tutorials for Neural Style transfert

• github: https://github.com/alexis-jacq/Pytorch-Tutorials

Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses

• arxiv: https://arxiv.org/abs/1701.08893

Arbitrary Style Transfer In Real-Time With Adaptive Instance Normalization

• intro: ICCV 2017. Cornell University
• paper: https://openreview.net/pdf?id=B1fUVMzKg
• github(Torch): https://github.com/xunhuang1995/AdaIN-style
• github(TensorFlow): https://github.com/elleryqueenhomels/arbitrary_style_transfer

Picking an optimizer for Style Transfer

• blog: https://medium.com/slavv/picking-an-optimizer-for-style-transfer-86e7b8cba84b#.cgv2oreaq
• github: https://github.com/slavivanov/Style-Tranfer

Multi-style Generative Network for Real-time Transfer

https://arxiv.org/abs/1703.06953

Deep Photo Style Transfer

• arxiv: https://arxiv.org/abs/1703.07511
• github(Torch): https://github.com/luanfujun/deep-photo-styletransfer
• github(Docker): https://github.com/martinbenson/deep-photo-styletransfer

Lightweight Neural Style on Pytorch

https://github.com/lizeng614/SqueezeNet-Neural-Style-Pytorch

StyleBank: An Explicit Representation for Neural Image Style Transfer

• intro: CVPR 2017
• arxiv: https://arxiv.org/abs/1703.09210

How to Make an Image More Memorable? A Deep Style Transfer Approach

• intro: ACM ICMR 2017
• arxiv: https://arxiv.org/abs/1704.01745

Visual Attribute Transfer through Deep Image Analogy

• intro: SIGGRAPH 2017
• keywords: Deep Image Analogy
• arxiv: https://arxiv.org/abs/1705.01088
• github: https://github.com/msracver/Deep-Image-Analogy

Characterizing and Improving Stability in Neural Style Transfer

https://arxiv.org/abs/1705.02092

Towards Metamerism via Foveated Style Transfer

https://arxiv.org/abs/1705.10041

Style Transfer for Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN

https://arxiv.org/abs/1706.03319

Meta Networks for Neural Style Transfer

• arxiv: https://arxiv.org/abs/1709.04111
• github: https://github.com/FalongShen/styletransfer

Neural Color Transfer between Images

• intro: Hong Kong University of Science and Technology & Microsoft Research
• arxiv: https://arxiv.org/abs/1710.00756

Improved Style Transfer by Respecting Inter-layer Correlations

https://arxiv.org/abs/1801.01933

Face Destylization

https://arxiv.org/abs/1802.01237

Unsupervised Typography Transfer

https://arxiv.org/abs/1802.02595

Stereoscopic Neural Style Transfer

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1802.10591

Arbitrary Style Transfer with Deep Feature Reshuffle

https://arxiv.org/abs/1805.04103

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

• intro: CVPR 2018. CUHK & SenseTime
• arxiv: https://arxiv.org/abs/1805.03857

Beyond Textures: Learning from Multi-domain Artistic Images for Arbitrary Style Transfer

https://arxiv.org/abs/1805.09987

A Comprehensive Comparison between Neural Style Transfer and Universal Style Transfer

https://arxiv.org/abs/1806.00868

Unbiased Image Style Transfer

https://arxiv.org/abs/1807.01424

Uncorrelated Feature Encoding for Faster Image Style Transfer

https://arxiv.org/abs/1807.01493

Adjustable Real-time Style Transfer

• intro: University of Illinois at Urbana-Champaign && Google Brain
• arxiv: https://arxiv.org/abs/1811.08560

Automated Deep Photo Style Transfer

• intro: University of Tubingen
• arxiv: https://arxiv.org/abs/1901.03915

Attention-aware Multi-stroke Style Transfer

https://arxiv.org/abs/1901.05127

StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

https://arxiv.org/abs/1906.02470

StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

https://arxiv.org/abs/1906.02470

Neural Art On Audio

MSc AI Project on generative deep networks and neural style transfer for audio

• github: https://github.com/Fr-d-rik/generative_audio
• project report: https://github.com/Fr-d-rik/generative_audio/blob/master/docs/project_report.pdf

Neural Song Style

• intro: Audio style transfer AI
• github: https://github.com/rupeshs/neuralsongstyle

Time Domain Neural Audio Style Transfer

• intro: NIPS 2017
• arxiv: https://arxiv.org/abs/1711.11160
• github: https://github.com//pkmital/time-domain-neural-audio-style-transfer

Learning Linear Transformations for Fast Arbitrary Style Transfer

https://arxiv.org/abs/1808.04537

Neural Art On Video

neural-style-video

• blog: http://larseidnes.com/2015/12/18/painting-videos-with-neural-networks/
• github: https://github.com/larspars/neural-style-video

Instructions for making a Neural-Style movie

• website: https://gist.github.com/genekogan/d61c8010d470e1dbe15d
• sample: https://vimeo.com/139123754

Artistic style transfer for videos

• arxiv: http://arxiv.org/abs/1604.08610
• github: https://github.com/manuelruder/artistic-videos

Artistic style transfer for videos and spherical images

https://arxiv.org/abs/1708.04538

How Deep Learning Can Paint Videos in the Style of Art’s Great Masters

• blog: https://blogs.nvidia.com/blog/2016/05/25/deep-learning-paints-videos/

DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies

• arxiv: http://arxiv.org/abs/1605.08153

Coherent Online Video Style Transfer

https://arxiv.org/abs/1703.09211

Laplacian-Steered Neural Style Transfer

• intro: ACM Multimedia Conference (MM) 2017
• arxiv: https://arxiv.org/abs/1707.01253

Real-Time Neural Style Transfer for Videos

• intro: Tsinghua University & Tencent AI Lab
• paper: http://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Real-Time_Neural_Style_CVPR_2017_paper.pdf

Multi-Content GAN for Few-Shot Font Style Transfer

https://arxiv.org/abs/1712.00516

Deep Painterly Harmonization

• arxiv: https://arxiv.org/abs/1804.03189
• github: https://github.com/luanfujun/deep-painterly-harmonization

ReCoNet: Real-time Coherent Video Style Transfer Network

• intro: The University of Hong Kong
• arixv: https://arxiv.org/abs/1807.01197
• supp: https://www.dropbox.com/s/go6f7uopjjsala7/ReCoNet%20Supplementary%20Material.pdf?dl=0

Fully-Featured Attribute Transfer

https://arxiv.org/abs/1902.06258

Neural Doodle

Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks

• paper: http://nucl.ai/semantic-style-transfer.pdf
• reddit: https://www.reddit.com/r/MachineLearning/comments/48zstj/my_wip_implementation_of_neural_image_analogies/
• github: https://github.com/alexjc/neural-doodle

Neural Doodle

• github: https://github.com/alexjc/neural-doodle

Faster neural doodle

• github: https://github.com/DmitryUlyanov/fast-neural-doodle

Feed-forward neural doodle

• blog: http://dmitryulyanov.github.io/feed-forward-neural-doodle/
• github: https://github.com/DmitryUlyanov/online-neural-doodle
• demo: http://likemo.net/

neural image analogies: Generate image analogies using neural matching and blending

• github: https://github.com/awentzonline/image-analogies

Neural doodle with Keras

https://github.com/fchollet/keras/blob/master/examples/neural_doodle.py

Deep Dreams

deepdream

• github: https://github.com/google/deepdream

cnn-vis: Use CNNs to generate images

• github: https://github.com/jcjohnson/cnn-vis

bat-country: A lightweight, extendible, easy to use Python package for deep dreaming and image generation with Caffe and CNNs

• github: https://github.com/jrosebr1/bat-country

DeepDreaming with TensorFlow

• ipn: http://nbviewer.jupyter.org/github/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb

deepdraw

• github: https://github.com/auduno/deepdraw

Understanding Deep Dreams

• blog: http://www.alanzucconi.com/2015/07/06/live-your-deepdream-how-to-recreate-the-inceptionism-effect/

Generating Deep Dreams

• blog：http://www.alanzucconi.com/2016/05/25/generating-deep-dreams/

Audio Deepdream: Optimizing Raw Audio With Convolutional Networks

• intro: Google Brain
• paper: https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/08/ardila-audio.pdf
• examples: https://drive.google.com/drive/folders/0B7NUtSSG_AgqZWF1ajdhSjhEMlk

Image Stylization

Automatic Portrait Segmentation for Image Stylization

• intro: The Chinese University of Hong Kong & Adobe Research
• project page(data+code): http://xiaoyongshen.me/webpage_portrait/index.html
• paper: http://www.cse.cuhk.edu.hk/leojia/papers/portrait_eg16.pdf
• github(Tensorflow): https://github.com/PetroWu/AutoPortraitMatting

Transfiguring Portraits

• paper: http://homes.cs.washington.edu/~kemelmi/Transfiguring_Portraits_Kemelmacher_SIGGRAPH2016.pdf

Stylize Aesthetic QR Code

• intro: Zhengzhou University & Zhejiang University
• arxiv: https://arxiv.org/abs/1803.01146