GAN is famous these days in the area of image processing for generating the unsupervised data. What can be the good sources to start studying the GAN and its applications.
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
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/
- Badges
- Science topic
- Similar topics
- Methodology
- Research Methodology
- Research Papers