Automatic Colorization of images using cGAN

Python code to convert hand drawn sketches into abstract art using GANs

Implemented and experimented with GAN, Conditional GAN and Deep-Convolutional GAN on various datasets for comparison, learning and demonstration purposes

Generate 256x256, 512x512 resolution images with simple Convolutional GAN by adding Gaussian noise to discriminator layers.

Manga Colorization and Style Transfer

Tạo màu cho ảnh xám sử dụng mạng đối nghịch tạo sinh có điều kiện.

GANs are cool

Ground motion simulation in the time-frequency domain by conditional GAN and phase retrieval

심화 R&E

Implementation of a cGAN to perform a data generation task on the CIFAR10 dataset. This generation can be used both to augment the original CIFAR10 dataset or to generate a new dataset, based on CIFAR10 classes, from scratch. It also has been implemented a pre-trained classifier in order to evaluate the performance of the cGAN model.

Lessons for training cGANs with embedding - housekeeping

Practice for GANs

This repository contains an implementation of a Generative Adversarial Network (GAN) trained on the Clothing MNIST dataset.

All GAN models in Keras

GAN Step By Step -- GSBS，顾名思义，我希望我自己能够一步一步的学习GAN。GAN 又名 生成对抗网络，是最近几年很热门的一种无监督算法，他能生成出非常逼真的照片，图像甚至视频。GAN是一个图像的全新的领域，从2014的GAN的发展现在，在计算机视觉中扮演这越来越重要的角色，并且到每年都能产出各色各样的东西，GAN的理论和发展都蛮多的。我感觉最近有很多人都在学习GAN，但是国内可能缺少比较多的GAN的理论及其实现，所以我也想着和大家一起学习，并且提供主流框架下 **pytorch,tensorflow,keras** 的一些实现教学。 在一个2016年的研讨会，`杨立昆`描述生成式对抗网络是“`机器学习这二十年来最酷的想法`”。

🎨Implementations of colorization algorithms.

Repository for (Un)Clear SoC Project, done in the Summer of 2021.

During my studies I had a lot of trouble finding a cDCGAN architecture that worked as I expected, so I decided to write my own version, finding an alternative way to condition it.

This repository contains the code for the paper "Icon Generation with Conditional GANs".

CGAN for vehicle trajectories prediction