This is the Pytorch implementation of Universal Style Transfer via Feature Transforms.

PyTorch implementation of neural style transfer algorithm

Neural Style Transfer (pytorch ver.)

Computer vision and Deep learning in SRU

PyTorch code for our CVPR-20 paper "Collaborative Distillation for Ultra-Resolution Universal Style Transfer"

PyTorch implementation of "Universal Style Transfer via Feature Trasforms"

PyTorch implementation of Neural Style Transfer, Pix2Pix, CycleGAN, and Deep Dream!

Official implementation of "Artist Style Transfer Via Quadratic Potential"

MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer

Reconstruction of the original paper on neural style transfer (Gatys et al.). I've additionally included reconstruction scripts which allow you to reconstruct only the content or the style of the image - for better understanding of how NST works.

Code for "Jhamtani H.*, Gangal V.*, Hovy E. and Nyberg E. Shakespearizing Modern Language Using Copy-Enriched Sequence to Sequence Models" Workshop on Stylistic Variation, EMNLP 2017

Unity Post Processing with Convolution Neural Network

Generating Art with Convolutional Neural Networks

An implementation of "A Neural Algorithm of Artistic Style" in Keras

Reconstruction of the fast neural style transfer (Johnson et al.). Some portions of the paper have been improved by the follow-up work like the instance normalization, etc. Checkout transformer_net.py's header for details.

Notebooks and tools for generative modeling in PyTorch.

This is PyTorch Implementation of Neural Style Transfer Algorithm which is modified for Audios.

Fast Neural Style Transfer in Julia

Demonstration implementations of neural network image processing algorithms

PyTorch implementation of "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511

艺术风格转换

A toolkit for interpreting and analyzing neural networks (vision)

Infinite Zoom For Style Transfer

C++ implementation of neural networks library with Keras-like API. Contains majority of commonly used layers, losses and optimizers. Supports sequential and multi-input-output (flow) models. Supports single CPU, Multi-CPU and GPU tensor operations (using cuDNN and cuBLAS).

A website based on Neural Style Transfer

📄 PyTorch implementation of "A Neural Algorithm of Artistic Style" (arXiv:1508.06576)

Framework for Neural Style Transfer (NST) built upon PyTorch

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai