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Multi-style Generative Network for Real-time Transfer [arXiv] [project] Hang Zhang, Kristin Dana @article{zhang2017multistyle,
title={Multi-style Generative Network for Real-time Transfer},
author={Zhang, Hang and Dana, Kristin},
journal={arXiv preprint arXiv:1703.06953},
year={2017}
}
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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.
luarocks install https://raw.githubusercontent.com/zhanghang1989/MSG-Net/master/texture-scm-1.rockspec- Clone the repo and download pre-trained models
git clone [email protected]:zhanghang1989/MSG-Net.git cd MSG-Net/experiments bash models/download_models.sh
- Web Camera Demo
qlua webcam.lua
- Test on Image
th test.lua -input_image images/content/venice-boat.jpg -image_size 1024 eog stylized
Please follow this tutorial to train a new model.
- 03/20/2017 we have released the demo video.
- 03/24/2017 We have released ArXiv paper and test code with pre-trained models.
- 04/09/2017 We have released the training code.
- 04/24/2017 Please checkout our PyTorch implementation.
The code benefits from outstanding prior work and their implementations including:
- Texture Networks: Feed-forward Synthesis of Textures and Stylized Images by Ulyanov et al. ICML 2016. (code)
- Perceptual Losses for Real-Time Style Transfer and Super-Resolution by Johnson et al. ECCV 2016 (code)
- Image Style Transfer Using Convolutional Neural Networks by Gatys et al. CVPR 2016 and its torch implementation code by Johnson.