Neural-Style-Transfer-Papers-Code

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[OCT, 2017] a paper "Automatic Semantic Style Transfer using Deep Convolutional Neural Networks and Soft Masks"

News!

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[ ChipGAN ] ChipGAN: A Generative Adversarial Network for Chinese Ink Wash Painting Style Transfer. Paper
[CVPR 2018] Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration.Paper Code
[CVPR 2018] Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Paper Code
[CVPR 2018] Meta Networks for Neural Style Transfer Paper Code Caffe-based
[CVPR 2018] A Common Framework for Interactive Texture Transfer Paper
[CVPR 2018] Arbitrary Style Transfer with Deep Feature Reshuffle Paper
[CVPR 2018] Separating Style and Content for Generalized Style Transfer Paper
[CVPR 2018] Captioning Images with Style Transfer from Unaligned Text Corpora
[CVPR 2018] CartoonGAN: Generative Adversarial Networks for Photo Cartoonization Paper
[ECCV 2018] Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields Paper Code.

Citation

If you find this repository useful for your research, please cite

@article{zhao2017automatic,
  title={Automatic Semantic Style Transfer using Deep Convolutional Neural Networks and Soft Masks},
  author={Huihuang Zhao, Paul L. Rosin, Yu-Kun Lai},
  journal={arxiv.org/abs/1708.09641},
  year={2017} 
}

Below infromation is from https://github.com/ycjing/Neural-Style-Transfer-Papers

[Jan, 2018] a review paper "Neural Style Transfer: A Review"

:white_check_mark: Supplementary Materials

:white_check_mark: Pre-trained Models

:white_check_mark: Images (v2)

A Taxonomy of Current Methods

1. "Slow" Neural Methods Based On Online Image Optimization

1.1. Parametric "Slow" Neural Methods with Summary Statistics

:white_check_mark: [A Neural Algorithm of Artistic Style] [Paper] (First Neural Style Transfer Paper)

:sparkle: Code:

:white_check_mark: [Image Style Transfer Using Convolutional Neural Networks] [Paper] (CVPR 2016)

:white_check_mark: [Incorporating Long-range Consistency in CNN-based Texture Generation] [Paper] (ICLR 2017)

:sparkle: Code:

Theano-based

:white_check_mark: [Laplacian-Steered Neural Style Transfer] [Paper] (ACM MM 2017)

:sparkle: Code:

Torch-based & TensorFlow-based

:white_check_mark: [Demystifying Neural Style Transfer] [Paper] (Theoretical Explanation) (IJCAI 2017)

:sparkle: Code:

MXNet-based

:white_check_mark: [Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses] [Paper]

1.2. Non-parametric "Slow" Neural Methods with MRFs

:white_check_mark: [Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis] [Paper] (CVPR 2016)

:sparkle: Code:

Torch-based

2. "Fast" Neural Methods Based On Offline Model Optimization

2.1. Per-Style-Per-Model "Fast" Neural Methods

:white_check_mark: [Perceptual Losses for Real-Time Style Transfer and Super-Resolution] [Paper] (ECCV 2016)

:sparkle: Code:

:sparkle: Pre-trained Models:

:white_check_mark: [Texture Networks: Feed-forward Synthesis of Textures and Stylized Images] [Paper] (ICML 2016)

:sparkle: Code:

:white_check_mark: [Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks] [Paper] (ECCV 2016)

:sparkle: Code:

Torch-based

2.2. Multiple-Style-Per-Model "Fast" Neural Methods

:white_check_mark: [A Learned Representation for Artistic Style] [Paper] (ICLR 2017)

:sparkle: Code:

TensorFlow-based

:white_check_mark: [Multi-style Generative Network for Real-time Transfer] [Paper] （arXiv, 03/2017）

:sparkle: Code:

:white_check_mark: [Diversified Texture Synthesis With Feed-Forward Networks] [Paper] (CVPR 2017)

:sparkle: Code:

Torch-based

:white_check_mark: [StyleBank: An Explicit Representation for Neural Image Style Transfer] [Paper] (CVPR 2017)

2.3. Arbitrary-Style-Per-Model "Fast" Neural Methods

:white_check_mark: [Fast Patch-based Style Transfer of Arbitrary Style] [Paper]

:sparkle: Code:

Torch-based

:white_check_mark: [Exploring the Structure of a Real-time, Arbitrary Neural Artistic Stylization Network] [Paper] (BMVC 2017)

:sparkle: Code:

TensorFlow-based

:white_check_mark: [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization] [Paper] (ICCV 2017)

:sparkle: Code:

:white_check_mark: [Universal Style Transfer via Feature Transforms] [Paper] (NIPS 2017)

:sparkle: Code:

:white_check_mark: [Meta Networks for Neural Style Transfer] [Paper] (CVPR 2018)

:sparkle: Code:

Caffe-based

:white_check_mark: [ZM-Net: Real-time Zero-shot Image Manipulation Network] [Paper]

Improvements and Extensions

:white_check_mark: [Preserving Color in Neural Artistic Style Transfer] [Paper]

:white_check_mark: [Controlling Perceptual Factors in Neural Style Transfer] [Paper] (CVPR 2017)

:sparkle: Code:

Torch-based

:white_check_mark: [Content-Aware Neural Style Transfer] [Paper]

:white_check_mark: [Towards Deep Style Transfer: A Content-Aware Perspective] [Paper] (BMVC 2016)

:white_check_mark: [Neural Doodle_Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork] [Paper]

:white_check_mark: [Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artwork] [Paper]

:sparkle: Code:

Torch-based

:white_check_mark: [The Contextual Loss for Image Transformation with Non-Aligned Data] [Paper]

:sparkle: Code:

TensorFlow-based

:white_check_mark: [Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis] [Paper] (CVPR 2017)

:sparkle: Code:

Torch-based

:white_check_mark: [Instance Normalization：The Missing Ingredient for Fast Stylization] [Paper]

:sparkle: Code:

Torch-based

:white_check_mark: [Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer] [Paper] (CVPR 2017)

:sparkle: Code:

TensorFlow-based

:white_check_mark: [Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields] [Paper] (ECCV 2018)

:sparkle: Code:

TensorFlow-based

:white_check_mark: [Depth-Preserving Style Transfer] [Paper]

:sparkle: Code:

Torch-based

:white_check_mark: [Depth-Aware Neural Style Transfer] [Paper] (NPAR 2017)

:white_check_mark: [Neural Style Transfer: A Paradigm Shift for Image-based Artistic Rendering?] [Paper] (NPAR 2017)

:white_check_mark: [Pictory: Combining Neural Style Transfer and Image Filtering] [Paper] (ACM SIGGRAPH 2017 Appy Hour)

:white_check_mark: [Painting Style Transfer for Head Portraits Using Convolutional Neural Networks] [Paper] (SIGGRAPH 2016)

:white_check_mark: [Son of Zorn's Lemma Targeted Style Transfer Using Instance-aware Semantic Segmentation] [Paper] (ICASSP 2017)

:white_check_mark: [Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN] [Paper] (ACPR 2017)

:white_check_mark: [Artistic Style Transfer for Videos] [Paper] (GCPR 2016)

:sparkle: Code:

Torch-based

:white_check_mark: [DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies] [Paper]

:white_check_mark: [Characterizing and Improving Stability in Neural Style Transfer] [Paper]) (ICCV 2017)

:white_check_mark: [Coherent Online Video Style Transfer] [Paper] (ICCV 2017)

:white_check_mark: [Real-Time Neural Style Transfer for Videos] [Paper] (CVPR 2017)

:white_check_mark: [A Common Framework for Interactive Texture Transfer] [Paper] (CVPR 2018)

:white_check_mark: [Deep Photo Style Transfer] [Paper] (CVPR 2017)

:sparkle: Code:

:white_check_mark: [A Closed-form Solution to Photorealistic Image Stylization] [Paper]

:sparkle: Code:

PyTorch-based

:white_check_mark: [Decoder Network Over Lightweight Reconstructed Feature for Fast Semantic Style Transfer] [Paper] (ICCV 2017)

:white_check_mark: [Stereoscopic Neural Style Transfer] [Paper] (CVPR 2018)

:white_check_mark: [Awesome Typography: Statistics-based Text Effects Transfer] [Paper] (CVPR 2017)

:sparkle: Code:

Matlab-based

:white_check_mark: [Neural Font Style Transfer] [Paper] (ICDAR 2017)

:white_check_mark: [Rewrite: Neural Style Transfer For Chinese Fonts] [Project]

:white_check_mark: [Separating Style and Content for Generalized Style Transfer] [Paper] (CVPR 2018)

:white_check_mark: [Visual Attribute Transfer through Deep Image Analogy] [Paper] (SIGGRAPH 2017)

:sparkle: Code:

Caffe-based

:white_check_mark: [Fashion Style Generator] [Paper] (IJCAI 2017)

:white_check_mark: [Deep Painterly Harmonization] [Paper]

:sparkle: Code:

Torch-based

:white_check_mark: [Fast Face-Swap Using Convolutional Neural Networks] [Paper] (ICCV 2017)

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

Application

:white_check_mark: Prisma

:white_check_mark: Ostagram

:sparkle: Code:

Website code

:white_check_mark: Deep Forger

:white_check_mark: NeuralStyler

:white_check_mark: Style2Paints

:sparkle: Code:

Website code

Application Papers

:white_check_mark: [Bringing Impressionism to Life with Neural Style Transfer in Come Swim] [Paper]

:white_check_mark: [Imaging Novecento. A Mobile App for Automatic Recognition of Artworks and Transfer of Artistic Styles] [Paper]

:white_check_mark: [ProsumerFX: Mobile Design of Image Stylization Components] [Paper]

:white_check_mark: [Pictory - Neural Style Transfer and Editing with coreML] [Paper]

:white_check_mark: [Tiny Transform Net for Mobile Image Stylization] [Paper] (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]

Neural-Style-Transfer-Papers-Code
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Metadata

Neural-Style-Transfer-Papers-Code

News!

Citation

A Taxonomy of Current Methods

1. "Slow" Neural Methods Based On Online Image Optimization

1.1. Parametric "Slow" Neural Methods with Summary Statistics

1.2. Non-parametric "Slow" Neural Methods with MRFs

2. "Fast" Neural Methods Based On Offline Model Optimization

2.1. Per-Style-Per-Model "Fast" Neural Methods

2.2. Multiple-Style-Per-Model "Fast" Neural Methods

2.3. Arbitrary-Style-Per-Model "Fast" Neural Methods

Improvements and Extensions

Application

Application Papers

Blogs

← Metadata

Owner

Metadata

Neural-Style-Transfer-Papers-Code Neural-Style-Transfer-Papers-Code copied to clipboard

Metadata

Neural-Style-Transfer-Papers-Code

News!

Citation

A Taxonomy of Current Methods

1. "Slow" Neural Methods Based On Online Image Optimization

1.1. Parametric "Slow" Neural Methods with Summary Statistics

1.2. Non-parametric "Slow" Neural Methods with MRFs

2. "Fast" Neural Methods Based On Offline Model Optimization

2.1. Per-Style-Per-Model "Fast" Neural Methods

2.2. Multiple-Style-Per-Model "Fast" Neural Methods

2.3. Arbitrary-Style-Per-Model "Fast" Neural Methods

Improvements and Extensions

Application

Application Papers

Blogs

← Metadata

Owner

Metadata

Neural-Style-Transfer-Papers-Code
Neural-Style-Transfer-Papers-Code copied to clipboard