All-About-the-GANs
GAN(Generative Adversarial Networks)s are the models that used in unsupervised machine learning, implemented by a system of two neural networks competing against each other in a zero-sum game framework. It was introduced by Ian Goodfellow et al. in 2014.
The purpose of this repository is providing the curated list of the state-of-the-art works on the field of Generative Adversarial Networks since their introduction in 2014.
(Word Cloud of Title)
(Word Cloud of Category)
(Word cloud of Abbr. name)
It provides a list that merged information from various GAN lists and repositories as below:
:link: Reference repositories
- [GAN zoo] - A list of all named GANs! by hindupuravinash
- Delving deep into Generative Adversarial Networks (GANs) [Delving] by GKalliatakis
- Awesome GAN for Medical Imaging [Medical] by xinario
- [Adversarial Nets Papers] The classic about Generative Adversarial Networks
- [Really Awesome GAN] by nightrome
- [GANs Paper Collection] by shawnyuen
- [GAN awesome applications] by nashory
- [GAN timeline] by dongb5
- [GAN comparison without cherry-picking] by khanrc
- Collection of generative models in [Keras], [Pytorch version], [Tensorflow version], [Chainer version]
- [Tensor layer]
- [Tensor pack]
You can also check out the same data in a tabular format with functionality to filter by year or do a quick search by title here.
Contributions are welcome. Please contact me at hollobit@etri.re.kr or send a pull request. You can have to add links through pull requests or create an issue which something I missed or need to start a discussion.