I recommend towardsdatascience, as good and rich source. Most of its articles have their codes shared on Github.

https://towardsdatascience.com/understanding-generative-adversarial-networks-gans-cd6e4651a29

Arash Rabbani Thanks a lot for giving directions.

There are several good resources such as NIPS 2016 Tutorial, UCLA ACM AI tutorial, etc. Some of these tutorials are listed as follows:

https://github.com/uclaacmai/Generative-Adversarial-Network-Tutorial

Article NIPS 2016 Tutorial: Generative Adversarial Networks

https://pathmind.com/wiki/generative-adversarial-network-gan

https://towardsdatascience.com/generative-adversarial-network-gan-for-dummies-a-step-by-step-tutorial-fdefff170391

There are some good research paper and blogs to learn GAN and its applications.

Go for survey (review) papers on GAN to go through current development in field of GAN.

Some papers of your reference are:

http://ieeexplore.ieee.org/document/8100115/

Article Recent Progress on Generative Adversarial Networks (GANs): A Survey

Article Recent Advances of Generative Adversarial Networks in Computer Vision

Here are some links pf blogs that you can follow:

https://towardsdatascience.com/generative-adversarial-network-gan-for-dummies-a-step-by-step-tutorial-fdefff170391

https://machinelearningmastery.com/how-to-code-the-generative-adversarial-network-training-algorithm-and-loss-functions/

https://towardsdatascience.com/writing-your-first-generative-adversarial-network-with-keras-2d16fd8d4889

https://machinelearningmastery.com/how-to-implement-pix2pix-gan-models-from-scratch-with-keras/