neycyanshi

HyperGAN

Composable GAN framework with api and user interface

optnet

OptNet: Differentiable Optimization as a Layer in Neural Networks

qpth

A fast and differentiable QP solver for PyTorch.

cvpr15deepcompare

Code and models for "Learning to Compare Image Patches via Convolutional Neural Networks"

topicsne

t-SNE experiments in pytorch

context-encoder

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

srez

Image super-resolution through deep learning

NeuralImageSynthesis

Code to reproduce the results from the paper "Controlling Perceptual Factors in Neural Style Transfer" (https://arxiv.org/abs/1611.07865).

fast-style-transfer

TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

dashboard

Utilities and monitors for machine learning experiments, web client included.

2D-3D-Semantics

The data skeleton from Joint 2D-3D-Semantic Data for Indoor Scene Understanding

pix2pix-tensorflow

Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/

MarrRevisited

Marr Revisited: 2D-3D Alignment via Surface Normal Prediction

pose-hg-demo

Code to test and use the model from "Stacked Hourglass Networks for Human Pose Estimation"

pix2pix

Image-to-image translation with conditional adversarial nets

CNNMRF

code for paper "Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis"

openface

Face recognition with deep neural networks.

fast-neural-style

Feedforward style transfer

FCRN-DepthPrediction

Deeper Depth Prediction with Fully Convolutional Residual Networks (FCRN)

SeetaFaceEngine

lsgan

This is the project for LS-GAN (Loss-Sensitive GAN)

PyTorch-Mini-Tutorials

Minimal tutorials for PyTorch

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

dcgan.torch

A torch implementation of http://arxiv.org/abs/1511.06434

nips2016

Learning What and Where to Draw

WassersteinGAN

CodingInterviews

剑指Offer——名企面试官精讲典型编程题

Super-Resolution-using-Generative-Adversarial-Networks

An implementation of SRGAN model in Keras

SRGAN

Implementation of [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802v2]