TF 2 examples: https://github.com/YunYang1994/TensorFlow2.0-Examples
ml5.js, Javascript interface to TF: https://ml5js.org/
Toward multimodal image-to-image translation (with code): https://junyanz.github.io/BicycleGAN/
Cities with electronic circuits: https://www.rileynwong.com/blog/2019/3/5/circuit-cities-with-pix2pix-using-image-to-image-translation-with-generative-adversarial-networks-to-create-buildings-maps-and-satellite-images-from-circuit-boards
Invisible cities: https://opendot.github.io/ml4a-invisible-cities/implementation/
Architecture: https://developer.nvidia.com/blog/archigan-generative-stack-apartment-building-design/
Generate semantic images (paper): https://arxiv.org/pdf/1906.12195.pdf
Neural Cities (Jasper van Loenen): https://jaspervanloenen.com/neural-cities/
City2city: https://bland.website/city2city/
https://awesomeopensource.com/projects/pix2pix
https://www.makery.info/2017/04/25/intelligence-artificielle-top-10-des-protos-a-suivre/
https://blog.eduonix.com/artificial-intelligence/grand-finale-applications-gans/
Google Autodraw: https://www.autodraw.com/
https://ml4a.github.io/guides/Pix2Pix/
Memo Akten pix2pix with webcam: https://github.com/memo/webcam-pix2pix-tensorflow
Image to image:
CycleGAN (PyTorch): https://github.com/junyanz/CycleGAN
Cycle GAN in Tensorflow: https://github.com/leehomyc/cyclegan-1
Another implementation of CycleGAN: https://github.com/vanhuyz/CycleGAN-TensorFlow
Pix2pix HD: https://github.com/NVIDIA/pix2pixHD
GAN compression for Pix2pix: https://github.com/mit-han-lab/gan-compression
IGAN: https://github.com/junyanz/iGAN
DeepFace:
- Code: https://github.com/yuanxiaosc/DeepNude-an-Image-to-Image-technology
- Online demo: http://www.geometrylearning.com:3000/index_EN_621.html
DeepNude:
- https://github.com/yuanxiaosc/DeepNude-an-Image-to-Image-technology/tree/master/DeepNude_software_itself
- With PyTorch, no watermark: https://github.com/zhengyima/DeepNude_NoWatermark_withModel
Unsupervised, MUNIT: https://github.com/taki0112/MUNIT-Tensorflow
Unsupervised, UNIT: https://github.com/mingyuliutw/UNIT
Collection of GAN implementations: https://github.com/tjwei/GANotebooks
Unity:
- Pix2pix: https://github.com/keijiro/Pix2Pix
- Generative cities: https://github.com/DerTarchin/Pix2Pix-Generative-Cities
Visual Objects Network (3D shapes): https://github.com/junyanz/VON
Next frame prediction: https://coxlab.github.io/prednet/
Nvidia AI generated game (vid2vid):
- Article: https://www.theverge.com/2018/12/3/18121198/ai-generated-video-game-graphics-nvidia-driving-demo-neurips
- Code: https://github.com/NVIDIA/vid2vid
Video generation from single image: https://github.com/malfusion/pix2pix-video-synthesis
Deblurring: https://github.com/KupynOrest/DeblurGAN
Monocular image to depth map: https://github.com/gautam678/Pix2Depth
Generating visual effects (with prebuilt executable): https://github.com/keijiro/Ngx
Movie colorizing: https://github.com/awjuliani/Pix2Pix-Film
Dehazing (paper): https://openaccess.thecvf.com/content_CVPR_2019/papers/Qu_Enhanced_Pix2pix_Dehazing_Network_CVPR_2019_paper.pdf
Labeled flowers: https://www.kaggle.com/alxmamaev/flowers-recognition/data
Page to page (with demo): https://github.com/lquirosd/P2PaLA
Handwriting synthesis:
Text to image synthesis: https://github.com/zsdonghao/im2txt2im
Kaggle: https://www.kaggle.com/datasets
Spell (has a free plan): https://spell.ml/
Twilio (pay as you go): https://www.twilio.com/