Jun-Yan Zhu's starred repositories
pytorch-CycleGAN-and-pix2pix
Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more)
PyTorch-progressive_growing_of_gans
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.
SoundSynth
Code for sound synthesis
3dgan-release
3D Generative Adversarial Network
PerceptualSimilarity
LPIPS metric. pip install lpips
BicycleGAN
Toward Multimodal Image-to-Image Translation
prog_gans_pytorch_inference
PyTorch inference for "Progressive Growing of GANs" with CelebA snapshot
progressive_growing_of_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
light-field-video
Light field video applications (e.g. video refocusing, focus tracking, changing aperture and view)
interactive-deep-colorization
Deep learning software for colorizing black and white images with a few clicks.
stn.pytorch
pytorch version of spatial transformer networks
SfMLearner
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
deep-photo-styletransfer
Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511
CatterPlots
Did you ever wish you could make scatter plots with cat shaped points? Now you can!
pix2pix-tensorflow
Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/
splitbrainauto
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.
pix2pix-tensorflow
TensorFlow implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
context-encoder
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
improved-gan
Code for the paper "Improved Techniques for Training GANs"
appearance-flow
A deep learning framework for synthesizing novel views of objects and scenes