Deep-Image-Analogy - The source code of 'Visual Attribute Transfer through Deep Image Analogy'.

•    C++

The major contributors of this repository include Jing Liao, Yuan Yao, Lu Yuan, Gang Hua and Sing Bing Kang at Microsoft Research. Deep Image Analogy is a technique to find semantically-meaningful dense correspondences between two input images. It adapts the notion of image analogy with features extracted from a Deep Convolutional Neural Network.

neural-style-tf - TensorFlow (Python API) implementation of Neural Style

•    Python

Additionally, techniques are presented for semantic segmentation and multiple style transfer. The relative weight of the style and content can be controlled.

texture_nets - Code for "Texture Networks: Feed-forward Synthesis of Textures and Stylized Images" paper

•    Lua

In the paper Texture Networks: Feed-forward Synthesis of Textures and Stylized Images we describe a faster way to generate textures and stylize images. It requires learning a feedforward generator with a loss function proposed by Gatys et al.. When the model is trained, a texture sample or stylized image of any size can be generated instantly. Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis presents a better architectural design for the generator network. By switching batch_norm to Instance Norm we facilitate the learning process resulting in much better quality.

zhihu - This repo contains the source code in my personal column (https://zhuanlan

•    Jupyter

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

arbitrary-image-stylization-tfjs - Arbitrary style transfer using TensorFlow.js

•    Javascript

This repository contains an implementation of arbitrary style transfer running fully inside the browser using TensorFlow.js. This is an implementation of an arbitrary style transfer algorithm running purely in the browser using TensorFlow.js. As with all neural style transfer algorithms, a neural network attempts to "draw" one picture, the Content (usually a photograph), in the style of another, the Style (usually a painting).

neural-style-audio-tf - TensorFlow implementation for audio neural style.

•    Jupyter

This is a TensorFlow reimplementation of Vadim's Lasagne code for style transfer algorithm for audio, which uses convolutions with random weights to represent audio features. To listen to examples go to the blog post. Also check out Torch implementation.

PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net

•    Jupyter

This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included by ModelDepot. We also provide Torch implementation and MXNet implementation. Image Style Transfer Using Convolutional Neural Networks by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge.

dreamsnap - Real life through the eyes of an artist

•    CSS

Real life through the eyes of an artist. This repo contains the landing page.

mace-models - Mobile AI Compute Engine Model Zoo

This project hosts Mobile AI Compute Engine (MACE) models. Each yml deployment script describes a case of deployments, which will generate one or one group (in case more than one ABIs specified) of static libraries and headers. To learn how to add new models, please refer to MACE documents.

Awesome_Neural_Style - A curated list of neural style and deep neural network visualization

a curated list of neural style and deep neural network visualization.

style-transfer - A Keras Implementation of "A Neural Algorithm of Artistic Style"

•    Python

This is a Keras implementation of A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge. Neural Styler lets you create artistic images by combining a base picture with the style of another. For example, the images above show multiple iterations of the Chicago skyline combined with Edvard Munch's The Scream.

neural_style_synthesizer

•    Python

The model files of neural networks are not contained in this repository. You can get them from nin_imagenet.caffemodel and VGG_ILSVRC_16_layers.caffemodel. Dependent libraries are installed with the following script.

neural-art-transfer - Tensorflow implementation of the paper "A Neural Algorithm of Artistic Style"

•    Python

This is my Tensorflow implementation of the Neural Style Transfer technique described in http://arxiv.org/abs/1508.06576 by Gatys et al. The implementation of this technique has been a very good way to learn Tensorflow. I have based my VGG model on the one provided here by Davi Frossard.

sketch-to-art - 🖼 Create artwork from your casual sketch with GAN and style transfer

•    Python

This project can transform your casual sketch to beautiful painting/artwork using modern AI technology. The principle behind this is called Conditional Adversarial Networks, known as pix2pix, which is able to generate image based on the given image.

neural-style-audio-torch - Torch implementation for audio neural style.

•    Lua

This is an extension of texture synthesis and style transfer method of Leon Gatys et al. based on Justin Johnson's code for neural style transfer. To listen to examples go to the blog post. Almost identical Lasagne implementation by Vadim Lebedev can be found here. Also check out TensorFlow implementation.

pytorch_cycle_gan - CycleGAN with Productive Generate APIs

•    Python

this repo based on the original implementation of CycleGAN: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix.git, in this version I reconstruct some code and made a generate API to simply generate image from your own single image and your trained model. I only trained about 50 epochs, but the result is fair enough for now. Laterly I will finish horse2zebra model, and update some more results.

style-transfer.js - 👨‍🎨️ Generate novel artistic images in Node.js

•    Javascript

Generate novel artistic images in Node.js, using TensorFlow.js.

MSG-Net - Multi-style Generative Network for Real-time Transfer

•    Lua

We also provide PyTorch implementation and MXNet implementation. Please install Torch7 with cuda and cudnn support. The code has been tested on Ubuntu 16.04 with Titan X Pascal and Maxwell. Please follow this tutorial to train a new model.

MXNet-Gluon-Style-Transfer - Neural Style and MSG-Net

•    Python

This repo has been included in official MXNet repo, which provides the implementations of MSG-Net and Neural Style Transfer. We also provide PyTorch and Torch implementations. A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge.

neural-style-pt - PyTorch implementation of neural style algorithm

•    Python

This is a PyTorch implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. The code is based on Justin Johnson's Neural-Style. By resizing the style image before extracting style features, we can control the types of artistic features that are transfered from the style image; you can control this behavior with the -style_scale flag. Below we see three examples of rendering the Golden Gate Bridge in the style of The Starry Night. From left to right, -style_scale is 2.0, 1.0, and 0.5.