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:pencil2: Neural Style Transfer: A Review
https://github.com/ycjing/Neural-Style-Transfer-Papers

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:pencil2: Neural Style Transfer: A Review

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# Neural-Style-Transfer-Papers :art:

Selected papers, corresponding codes and pre-trained models in our review paper **"Neural Style Transfer: A Review" [[arXiv Version]](https://arxiv.org/abs/1705.04058) [[IEEE Version]](https://ieeexplore.ieee.org/document/8732370)**



The corresponding OSF repository can be found at: https://osf.io/f8tu4/.



*If I missed your paper in this review, please email me or just pull a request here. I am more than happy to add it. Thanks!*



## Citation 

If you find this repository useful for your research, please consider citing



```

@article{jing2019neural,

  title={Neural Style Transfer: A Review},

  author={Jing, Yongcheng and Yang, Yezhou and Feng, Zunlei and Ye, Jingwen and Yu, Yizhou and Song, Mingli},

  journal={IEEE Transactions on Visualization and Computer Graphics},

  year={2019}

}

```

Please also consider citing our ECCV paper and AAAI (Oral) paper:



```

@inproceedings{jing2018stroke,

  title={Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields},

  author={Jing, Yongcheng and Liu, Yang and Yang, Yezhou and Feng, Zunlei and Yu, Yizhou and Tao, Dacheng and Song, Mingli},

  booktitle={ECCV},

  year={2018}

}

```

```

@inproceedings{jing2020dynamic,

  title={Dynamic Instance Normalization for Arbitrary Style Transfer},

  author={Jing, Yongcheng and Liu, Xiao and Ding, Yukang and Wang, Xinchao and Ding, Errui and Song, Mingli and Wen, Shilei},

  booktitle={AAAI},

  year={2020}

}

```



Thanks!



## Framework



There is a recent nice NST framework called [pystiche](https://github.com/ycjing/Neural-Style-Transfer-Papers/issues/17#issue-725784148), developed by [Philip Meier](https://github.com/pmeier). If you are interested, please refer to https://github.com/pmeier/pystiche. A package that comprises reference implementations of NST papers with pystiche can be found at [pystiche_papers](https://github.com/pmeier/pystiche_papers) (work in progress).



---



## *News!*



- [June, 2019] Update the *Images (TVCG)* (.png) and *Supplementary Material (TVCG)* in the *Materials*. **Warmly welcome to use *Images (TVCG)* for comparison results in your paper!**



- [May, 2019] Our paper *Neural Style Transfer: A Review* has been accepted by TVCG as a regular paper. This repository will be updated soon.



- [July, 2018] Our paper *Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields* has been accepted by ECCV 2018. Our review will be updated correspondingly.



- [June, 2018] Upload a new version of our paper on arXiv which adds several missing papers (e.g., the work of Wang et al. *ZM-Net: Real-time Zero-shot Image Manipulation Network*).



- [Apr, 2018] We have released a new version of the paper with significant changes at: https://arxiv.org/pdf/1705.04058.pdf  Appreciate the feedback!



- [Feb, 2018] Update the *Images* *(Images_neuralStyleTransferReview_v2)* in the *Materials*. Add the results of Li et al.'s NIPS 2017 paper.



- [Jan, 2018] *Pre-trained models* and all the *content images*, the *style images*, and the *stylized results* in the paper have been released.





    

    




## Materials corresponding to Our Paper



:white_check_mark: [**Supplementary Material (TVCG)**](https://drive.google.com/file/d/1_VTS4rUSl488wgSrz2K5BfKra33gvaHH/view?usp=sharing)



:white_check_mark: [**Pre-trained Models**](https://www.dropbox.com/s/37lje23pb75ecob/Models_neuralStyleTransferReview.zip?dl=0)



:white_check_mark: [**Images (TVCG)(.png)**](https://drive.google.com/file/d/14RN0GN09-rordzRqp4o8oU30BB7uiNcj/view?usp=sharing)



## A Taxonomy of Current Methods



### 1. Image-Optimisation-Based Online Neural Methods



###  1.1. Parametric Neural Methods with Summary Statistics



:white_check_mark: [**A Neural Algorithm of Artistic Style**] [[Paper]](https://arxiv.org/pdf/1508.06576.pdf) *(First Neural Style Transfer Paper)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/jcjohnson/neural-style)

*   [TensorFlow-based](https://github.com/anishathalye/neural-style)

*   [TensorFlow-based with L-BFGS optimizer support](https://github.com/cysmith/neural-style-tf)

*   [Caffe-based](https://github.com/fzliu/style-transfer) 

*   [Keras-based](https://github.com/titu1994/Neural-Style-Transfer)

*   [MXNet-based](https://github.com/pavelgonchar/neural-art-mini)

*   [MatConvNet-based](https://github.com/aravindhm/neural-style-matconvnet)



:white_check_mark: [**Image Style Transfer Using Convolutional Neural Networks**] [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf) *(CVPR 2016)*



:white_check_mark: [**Incorporating Long-range Consistency in CNN-based Texture Generation**] [[Paper]](https://arxiv.org/pdf/1606.01286.pdf)  *(ICLR 2017)* 



:sparkle: **Code:**



*   [Theano-based](https://github.com/guillaumebrg/texture_generation)



:white_check_mark: [**Laplacian-Steered Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1707.01253.pdf)  *(ACM MM 2017)*



:sparkle: **Code:**



*   [Torch-based & TensorFlow-based](https://github.com/askerlee/lapstyle)



:white_check_mark: [**Demystifying Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1701.01036.pdf)  *(Theoretical Explanation)* *(IJCAI 2017)*



:sparkle: **Code:**



*   [MXNet-based](https://github.com/lyttonhao/Neural-Style-MMD)



:white_check_mark: [**Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses**] [[Paper]](https://arxiv.org/pdf/1701.08893.pdf)



###  1.2. Non-parametric Neural Methods with MRFs



:white_check_mark: [**Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis**] [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Li_Combining_Markov_Random_CVPR_2016_paper.pdf)  *(CVPR 2016)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/chuanli11/CNNMRF)



:white_check_mark: [**Arbitrary Style Transfer with Deep Feature Reshuffle**] [[Paper]](https://arxiv.org/pdf/1805.04103.pdf)  *(CVPR 2018)*



###  2. Model-Optimisation-Based Offline Neural Methods



### 2.1. Per-Style-Per-Model Neural Methods



:white_check_mark: [**Perceptual Losses for Real-Time Style Transfer and Super-Resolution**] [[Paper]](https://arxiv.org/pdf/1603.08155.pdf)  *(ECCV 2016)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/jcjohnson/fast-neural-style)

*   [TensorFlow-based](https://github.com/lengstrom/fast-style-transfer)

*   [Chainer-based](https://github.com/yusuketomoto/chainer-fast-neuralstyle)



:sparkle: **Pre-trained Models:**



*   [Torch-models](https://github.com/ProGamerGov/Torch-Models)

*   [Chainer-models](https://github.com/gafr/chainer-fast-neuralstyle-models)



:white_check_mark: [**Texture Networks: Feed-forward Synthesis of Textures and Stylized Images**] [[Paper]](http://www.jmlr.org/proceedings/papers/v48/ulyanov16.pdf)  *(ICML 2016)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/DmitryUlyanov/texture_nets)

*   [TensorFlow-based](https://github.com/tgyg-jegli/tf_texture_net)



:white_check_mark: [**Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks**] [[Paper]](https://arxiv.org/pdf/1604.04382.pdf)  *(ECCV 2016)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/chuanli11/MGANs)



### 2.2. Multiple-Style-Per-Model Neural Methods



:white_check_mark: [**A Learned Representation for Artistic Style**] [[Paper]](https://arxiv.org/pdf/1610.07629.pdf)  *(ICLR 2017)*



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/tensorflow/magenta/tree/master/magenta/models/image_stylization)



:white_check_mark: [**Multi-style Generative Network for Real-time Transfer**] [[Paper]](https://arxiv.org/pdf/1703.06953.pdf)  ***（arXiv, 03/2017）***



:sparkle: **Code:**



*   [PyTorch-based](https://github.com/zhanghang1989/PyTorch-Style-Transfer)

*   [Torch-based](https://github.com/zhanghang1989/MSG-Net)



:white_check_mark: [**Diversified Texture Synthesis With Feed-Forward Networks**] [[Paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Li_Diversified_Texture_Synthesis_CVPR_2017_paper.pdf)  *(CVPR 2017)* 



:sparkle: **Code:**



*   [Torch-based](https://github.com/Yijunmaverick/MultiTextureSynthesis)



:white_check_mark: [**StyleBank: An Explicit Representation for Neural Image Style Transfer**] [[Paper]](https://arxiv.org/pdf/1703.09210.pdf)  *(CVPR 2017)*



### 2.3. Arbitrary-Style-Per-Model Neural Methods



:white_check_mark: [**Fast Patch-based Style Transfer of Arbitrary Style**] [[Paper]](https://arxiv.org/pdf/1612.04337.pdf) 



:sparkle: **Code:**



*   [Torch-based](https://github.com/rtqichen/style-swap)



:white_check_mark: [**Exploring the Structure of a Real-time, Arbitrary Neural Artistic Stylization Network**] [[Paper]](https://arxiv.org/pdf/1705.06830.pdf)  *(BMVC 2017)*



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/tensorflow/magenta/tree/master/magenta/models/arbitrary_image_stylization)



:white_check_mark: [**Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization**] [[Paper]](https://arxiv.org/pdf/1703.06868.pdf)  *(ICCV 2017)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/xunhuang1995/AdaIN-style)

*   [TensorFlow-based with Keras](https://github.com/eridgd/AdaIN-TF)

*   [TensorFlow-based without Keras](https://github.com/elleryqueenhomels/arbitrary_style_transfer)



:white_check_mark: [**Dynamic Instance Normalization for Arbitrary Style Transfer**] [[Paper]](https://arxiv.org/pdf/1911.06953.pdf)  *(AAAI 2020)*



:white_check_mark: [**Universal Style Transfer via Feature Transforms**] [[Paper]](https://arxiv.org/pdf/1705.08086.pdf)  *(NIPS 2017)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/Yijunmaverick/UniversalStyleTransfer)

*   [TensorFlow-based](https://github.com/eridgd/WCT-TF)

*   [PyTorch-based #1](https://github.com/sunshineatnoon/PytorchWCT)

*   [PyTorch-based #2](https://github.com/pietrocarbo/deep-transfer)



:white_check_mark: [**Meta Networks for Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1709.04111.pdf)  *(CVPR 2018)*



:sparkle: **Code:**



*   [Caffe-based](https://github.com/FalongShen/styletransfer)



:white_check_mark: [**ZM-Net: Real-time Zero-shot Image Manipulation Network**] [[Paper]](https://arxiv.org/pdf/1703.07255.pdf)



:white_check_mark: [**Avatar-Net: Multi-Scale Zero-Shot Style Transfer by Feature Decoration**] [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/0137.pdf)  *(CVPR 2018)*



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/LucasSheng/avatar-net)



:white_check_mark: [**Learning Linear Transformations for Fast Arbitrary Style Transfer**] [[Paper]](https://arxiv.org/pdf/1808.04537.pdf)



:sparkle: **Code:**



*   [PyTorch-based](https://github.com/sunshineatnoon/LinearStyleTransfer)



## Improvements and Extensions



:white_check_mark: [**Preserving Color in Neural Artistic Style Transfer**] [[Paper]](https://arxiv.org/pdf/1606.05897.pdf) 



:white_check_mark: [**Controlling Perceptual Factors in Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1611.07865.pdf)  *(CVPR 2017)* 



:sparkle: **Code:**



*   [Torch-based](https://github.com/leongatys/NeuralImageSynthesis)



:white_check_mark: [**Content-Aware Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1601.04568.pdf) 



:white_check_mark: [**Towards Deep Style Transfer: A Content-Aware Perspective**] [[Paper]](http://www.bmva.org/bmvc/2016/papers/paper008/paper008.pdf)  *(BMVC 2016)*



:white_check_mark: [**Neural Doodle_Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork**] [[Paper]](https://arxiv.org/pdf/1603.01768.pdf) 



:white_check_mark: [**Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork**] [[Paper]](https://arxiv.org/pdf/1603.01768.pdf) 



:sparkle: **Code:**



*   [Torch-based](https://github.com/alexjc/neural-doodle)



:white_check_mark: [**The Contextual Loss for Image Transformation with Non-Aligned Data**] [[Paper]](https://arxiv.org/pdf/1803.02077)   *(ECCV 2018)* 



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/roimehrez/contextualLoss)



:white_check_mark: [**Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis**] [[Paper]](https://arxiv.org/pdf/1701.02096.pdf)  *(CVPR 2017)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/DmitryUlyanov/texture_nets)



:white_check_mark: [**Instance Normalization：The Missing Ingredient for Fast Stylization**] [[Paper]](https://arxiv.org/pdf/1607.08022.pdf) 



:sparkle: **Code:**



*   [Torch-based](https://github.com/DmitryUlyanov/texture_nets)



:white_check_mark: [**A Style-Aware Content Loss for Real-time HD Style Transfer**] [[Paper]](https://arxiv.org/pdf/1807.10201)  *(ECCV 2018)* 



:white_check_mark: [**Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer**] [[Paper]](https://arxiv.org/pdf/1612.01895.pdf)  *(CVPR 2017)* 



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/fullfanta/multimodal_transfer)



:white_check_mark: [**Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields**] [[Paper]](https://arxiv.org/pdf/1802.07101.pdf)  *(ECCV 2018)* 



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/LouieYang/stroke-controllable-fast-style-transfer)



:white_check_mark: [**Depth-Preserving Style Transfer**] [[Paper]](https://github.com/xiumingzhang/depth-preserving-neural-style-transfer/blob/master/report/egpaper_final.pdf) 



:sparkle: **Code:**



*   [Torch-based](https://github.com/xiumingzhang/depth-preserving-neural-style-transfer)



:white_check_mark: [**Depth-Aware Neural Style Transfer**] [[Paper]](https://dl.acm.org/citation.cfm?id=3092924)  *(NPAR 2017)*



:white_check_mark: [**Neural Style Transfer: A Paradigm Shift for Image-based Artistic Rendering?**] [[Paper]](https://tobias.isenberg.cc/personal/papers/Semmo_2017_NST.pdf)  *(NPAR 2017)*



:white_check_mark: [**Pictory: Combining Neural Style Transfer and Image Filtering**] [[Paper]](https://www.researchgate.net/publication/320035123_Demo_Pictory_-_Neural_Style_Transfer_and_Editing_with_CoreML)  *(ACM SIGGRAPH 2017 Appy Hour)*



:white_check_mark: [**Painting Style Transfer for Head Portraits Using Convolutional Neural Networks**] [[Paper]](http://dl.acm.org/citation.cfm?id=2925968)  *(SIGGRAPH 2016)*



:white_check_mark: [**Son of Zorn's Lemma Targeted Style Transfer Using Instance-aware Semantic Segmentation**] [[Paper]](https://arxiv.org/pdf/1701.02357.pdf)  *(ICASSP 2017)*



:white_check_mark: [**Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN**] [[Paper]](https://arxiv.org/pdf/1706.03319.pdf)  *(ACPR 2017)*



:white_check_mark: [**Artistic Style Transfer for Videos**] [[Paper]](https://arxiv.org/pdf/1604.08610.pdf)  *(GCPR 2016)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/manuelruder/artistic-videos)



:white_check_mark: [**DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies**] [[Paper]](https://arxiv.org/pdf/1605.08153.pdf) 



:white_check_mark: [**Characterizing and Improving Stability in Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1705.02092.pdf))  *(ICCV 2017)*



:white_check_mark: [**Coherent Online Video Style Transfer**] [[Paper]](https://arxiv.org/pdf/1703.09211.pdf)  *(ICCV 2017)*  



:white_check_mark: [**Real-Time Neural Style Transfer for Videos**] [[Paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Real-Time_Neural_Style_CVPR_2017_paper.pdf)  *(CVPR 2017)* 



:white_check_mark: [**A Common Framework for Interactive Texture Transfer**] [[Paper]](http://www.icst.pku.edu.cn/F/zLian/papers/CVPR18-Men.pdf)  *(CVPR 2018)*



:white_check_mark: [**Deep Photo Style Transfer**] [[Paper]](https://arxiv.org/pdf/1703.07511.pdf)  *(CVPR 2017)*



:sparkle: **Code:**



*   [Torch-based](https://github.com/luanfujun/deep-photo-styletransfer)

*   [TensorFlow-based](https://github.com/LouieYang/deep-photo-styletransfer-tf)



:white_check_mark: [**A Closed-form Solution to Photorealistic Image Stylization**] [[Paper]](https://arxiv.org/pdf/1802.06474.pdf)  *(ECCV 2018)* 



:sparkle: **Code:**



*   [PyTorch-based](https://github.com/NVIDIA/FastPhotoStyle)



:white_check_mark: [**Photorealistic Style Transfer via Wavelet Transforms**] [[Paper]](https://arxiv.org/pdf/1903.09760.pdf)



:sparkle: **Code:**



*   [PyTorch-based](https://github.com/clovaai/WCT2)



:white_check_mark: [**Decoder Network Over Lightweight Reconstructed Feature for Fast Semantic Style Transfer**] [[Paper]](http://feng-xu.com/papers/iccv2017_style.pdf)  *(ICCV 2017)* 



:white_check_mark: [**Stereoscopic Neural Style Transfer**] [[Paper]](https://arxiv.org/pdf/1802.10591.pdf)  *(CVPR 2018)* 



:white_check_mark:   [**Awesome Typography: Statistics-based Text Effects Transfer**] [[Paper]](https://arxiv.org/abs/1611.09026)  *(CVPR 2017)*



:sparkle: **Code:**



*   [Matlab-based](https://github.com/williamyang1991/Text-Effects-Transfer)



:white_check_mark:   [**Neural Font Style Transfer**] [[Paper]](http://ieeexplore.ieee.org/document/8270274/)  *(ICDAR 2017)* 



:white_check_mark:   [**Rewrite: Neural Style Transfer For Chinese Fonts**] [[Project]](https://github.com/kaonashi-tyc/Rewrite)



:white_check_mark:   [**Separating Style and Content for Generalized Style Transfer**] [[Paper]](https://arxiv.org/pdf/1711.06454.pdf)  *(CVPR 2018)*  



:white_check_mark: [**Visual Attribute Transfer through Deep Image Analogy**] [[Paper]](https://arxiv.org/pdf/1705.01088.pdf)  *(SIGGRAPH 2017)*



:sparkle: **Code:**



*   [Caffe-based](https://github.com/msracver/Deep-Image-Analogy)



:white_check_mark: [**Fashion Style Generator**] [[Paper]](https://www.ijcai.org/proceedings/2017/0520.pdf)  *(IJCAI 2017)*



:white_check_mark: [**Deep Painterly Harmonization**] [[Paper]](https://arxiv.org/abs/1804.03189)



:sparkle: **Code:**



*   [Torch-based](https://github.com/luanfujun/deep-painterly-harmonization)



:white_check_mark: [**Fast Face-Swap Using Convolutional Neural Networks**] [[Paper]](http://openaccess.thecvf.com/content_ICCV_2017/papers/Korshunova_Fast_Face-Swap_Using_ICCV_2017_paper.pdf)  *(ICCV 2017)*



:white_check_mark: [**Learning Selfie-Friendly Abstraction from Artistic Style Images**] [[Paper]]()  *(ACML 2018)*



:white_check_mark: [**Style Transfer with Adaptation to the Central Objects of the Scene**] [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-30425-6_40)  *(NEUROINFORMATICS 2019)*



## Application



:white_check_mark: [**Prisma**](https://prisma-ai.com/) 



:white_check_mark: [**Ostagram**](https://ostagram.ru/) 



:white_check_mark: [**AlterDraw**](https://alterdraw.com/en/)



:white_check_mark: [**Vinci**](https://play.google.com/store/apps/details?id=io.vinci.android&hl=en_US&gl=US)



:white_check_mark: [**Artisto**](https://en.wikipedia.org/wiki/Artisto)



:sparkle: **Code:**



*   [Website code](https://github.com/SergeyMorugin/ostagram)



:white_check_mark: [**Deep Forger**](https://deepforger.com/) 



:white_check_mark: [**NeuralStyler**](http://neuralstyler.com/) 



:white_check_mark: [**Style2Paints**](http://paintstransfer.com/) 



:sparkle: **Code:**



*   [Website code](https://github.com/lllyasviel/style2paints)



## Application Papers



:white_check_mark: [**Bringing Impressionism to Life with Neural Style Transfer in Come Swim**] [[Paper]](https://arxiv.org/pdf/1701.04928.pdf) 



:white_check_mark: [**Imaging Novecento. A Mobile App for Automatic Recognition of Artworks and Transfer of Artistic Styles**] [[Paper]](https://www.micc.unifi.it/wp-content/uploads/2017/01/imaging900.pdf) 



:white_check_mark: [**ProsumerFX: Mobile Design of Image Stylization Components**] [[Paper]](https://www.researchgate.net/publication/319631844_ProsumerFX_Mobile_Design_of_Image_Stylization_Components)



:white_check_mark: [**Pictory - Neural Style Transfer and Editing with coreML**] [[Paper]](https://www.researchgate.net/publication/320035123_Demo_Pictory_-_Neural_Style_Transfer_and_Editing_with_CoreML)



:white_check_mark: [**Tiny Transform Net for Mobile Image Stylization**] [[Paper]](https://dl.acm.org/citation.cfm?id=3079034)  *(ICMR 2017)*



## Blogs 



:white_check_mark: [**Caffe2Go**][https://code.facebook.com/posts/196146247499076/delivering-real-time-ai-in-the-palm-of-your-hand/]



:white_check_mark: [**Supercharging Style Transfer**][https://research.googleblog.com/2016/10/supercharging-style-transfer.html]



:white_check_mark: [**Issue of Layer Chosen Strategy**][http://yongchengjing.com/pdf/Issue_layerChosenStrategy_neuralStyleTransfer.pdf]



:white_check_mark: [**Picking an optimizer for Style Transfer**][https://blog.slavv.com/picking-an-optimizer-for-style-transfer-86e7b8cba84b]



:white_check_mark: [**Enhanced Color Style Transfer (Photo-surrealism Style Transfer)**] [[Project]](https://github.com/TJCoding/Enhanced-Image-Colour-Transfer)



## Others



:white_check_mark: [**Conditional Fast Style Transfer Network**] [[Paper]](http://img.cs.uec.ac.jp/pub/conf17/170612yanai_0.pdf)



:white_check_mark: [**Unseen Style Transfer Based on a Conditional Fast Style Transfer Network**] [[Paper]](https://openreview.net/forum?id=H1Y7-1HYg&noteId=H1Y7-1HYg)



:white_check_mark: [**DeepStyleCam: A Real-time Style Transfer App on iOS**] [[Paper]](http://img.cs.uec.ac.jp/pub/conf16/170103tanno_0.pdf)



:white_check_mark: [**Deep Feature Rotation for Multimodal Image Style Transfer**] [[Paper]](https://arxiv.org/pdf/2202.04426.pdf)  *(NICS 2021)*



:sparkle: **Code:**



*   [TensorFlow-based](https://github.com/sonnguyen129/deep-feature-rotation)