This is the Pytorch implementation of "Learning Linear Transformations for Fast Arbitrary Style Transfer". https://github.com/sunshineatnoon/LinearStyleTransfer
基于TensorFlow.js的画风迁移演示 https://github.com/reiinakano/arbitrary-image-stylization-tfjs
Style transfer, deep learning, feature transform https://github.com/NVIDIA/FastPhotoStyle
Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189 https://github.com/luanfujun/deep-painterly-harmonization
快速地转换任何图像的风格。据该项目自己的测试，在2015 Titan X显卡上将一幅MIT Stata Center的照片(1024x680)转换成弗朗西斯·毕卡比亚（Francis Picabia）的油画《Udnie》的风格只需要100毫秒。其速度之快甚至可以逐帧转换视频并合成一个可以播放的视频。 https://github.com/lengstrom/fast-style-transfer
Style2Paints基于TesnorFlow，可以根据给出的样例给素描线稿上色，甚至可以不参照任何样例自行决定上色方案 https://github.com/lllyasviel/style2paints
这个项目是PyTorch版的CycleGAN。CycleGAN利用对抗式生成网络实现图像到图像的转换，例如将莫奈、梵高的油画转换成风景照片，将夏季的照片转换成冬季，将照片中的苹果转换成橙子等。作者的网站上有更为详细的介绍(https://junyanz.github.io/CycleGAN/)。 https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
Pix2PixHD是高清照片级图像转换(https://arxiv.org/pdf/1711.11585.pdf)的pytorch实现。它可以将标签图转换成照片级别的图像，或根据面部标签图合成人物肖像。 https://github.com/NVIDIA/pix2pixHD
利用深度神经网络对声音进行风格转换。虽然还不完善，但该项目已经实现了将任意声音转换为凯特·温斯莱特的声音。 https://github.com/andabi/deep-voice-conversion
深度学习老照片自动着色与修复 https://github.com/jantic/DeOldify https://colab.research.google.com/github/jantic/DeOldify/blob/master/DeOldify_colab.ipynb
CartoonGAN: Generative Adversarial Networks for Photo Cartoonization https://github.com/znxlwm/pytorch-CartoonGAN
MetaStyle: Three-Way Trade-Off Among Speed, Flexibility, and Quality in Neural Style Transfer https://github.com/WellyZhang/MetaStyle
人人都能成为艺术家，用python+OpenCV实现世界名画风格迁移 https://mbd.baidu.com/newspage/data/landingshare?pageType=1&isBdboxFrom=1&context=%7B%22nid%22%3A%22news_9130260126327074330%22%2C%22sourceFrom%22%3A%22bjh%22%7D
deep-painterly-harmonization 一个基于深度学习的开源项目，让图片可以毫无违和感的融入到绘画作品中 https://arxiv.org/abs/1804.03189 https://github.com/luanfujun/deep-painterly-harmonization
deep-photo-styletransfer 一个基于深度学习的开源项目，利用了深度卷积网络来进行摄影风格转换，瞬间切换图片风格 https://github.com/luanfujun/deep-photo-styletransfer
Learning multi-domain multi-modality I2I translation https://github.com/HsinYingLee/MDMM
Attention-aware Multi-stroke Style Transfer https://github.com/JianqiangRen/AAMS
PyTorch implementation of the Delete, Retrieve Generate style transfer algorithm https://github.com/rpryzant/delete_retrieve_generate
Photorealistic Style Transfer via Wavelet Transforms https://github.com/ClovaAI/WCT2
Style Transfer by Relaxed Optimal Transport and Self-Similarity https://github.com/nkolkin13/STROTSS
https://github.com/mnicnc404/CartoonGan-tensorflow
ETNet: Error Transition Network for Arbitrary Style Transfer https://github.com/zhijieW94/ETNet
Content and Style Disentanglement for Artistic Style Transfer https://github.com/CompVis/content-style-disentangled-ST
用Python快速实现图片的风格迁移 https://mp.weixin.qq.com/s/A5hcU5kZlSW0qx6BJ5UIyA
Realtime Coherent Style Transfer for Videos https://github.com/safwankdb/ReCoNet-PyTorch
Don't Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation https://arxiv.org/abs/1907.11004
End-to-end Projector Photometric Compensation (CVPR'19 Oral) https://github.com/BingyaoHuang/CompenNet
Ebsynth：快速示例图片合成与画风迁移 https://github.com/jamriska/ebsynth
对抗鲁棒分类器神经网络画风迁移 https://reiinakano.com/2019/06/21/robust-neural-style-transfer.html