Table of Contents Introductory Explanation of GANs Applications of GANs GANs for Image Editing Using GANs for Security Generating Data using GANs GANs for Attention Prediction GANs for 3D Object Generation Introductory Explanation of GANs Right, we have a sense of what GANs can do.
But how do they work?.What goes on underneath all the wonderful applications this powerful algorithm produces?.Let’s understand this using a popular example.
There’s a forger (who creates fake artistry) and an investigator tasked with detecting these fake artworks.
The task of this forger is to create fraudulent imitations of original paintings by famous artists (like Leonardo Da Vinci).
If he/she can pass off this work as the original art piece, the forger can potentially net a lot of money.
On the other side of this situation, the art investigator’s task is to catch these forgers.
How does he/she do it?.The investigator knows what are the properties which set the original artist apart and what kind of painting he/she would have created.
The investigator leverages this knowledge against the piece at hand to check if it is real or not.
This contest of forger vs investigator goes on, which ultimately makes world-class investigators (and unfortunately world-class forgers); a battle between good and evil.
Now, consider both forger and investigator as robots.
When you train the forger to be a painter and the investigator to tell a fake painting from the real one – you now have an algorithmic painter at hand!.That’s essentially how GANs work on the inside.
Awesome, aren’t they?.I haven’t got into the intricate details of GANs here.
This is just the tip of the iceberg.
If you are interested in learning more about GANs, you should go through this article: An introductory guide to Generative Adversarial Networks (GANs) and their promise!. Applications of GANs Now that we have an intuition of how GANs work, let’s put on our exploration hats!.It’s time to dive into the interesting applications of GANs that are commonly used in the industry right now.
GANs for Image Editing Most image editing software these days don’t give us much flexibility to make creative changes in pictures.
For example, let’s say you want to change the appearance of a 90-year-old person by changing his/her hairstyle.
This can’t be done by the current image editing tools out there.
But guess what?.Using GANs, we can reconstruct images and attempt to change the appearance drastically.
This amazing paper demonstrates this very cutting edge application.
Another similar application is image de-raining (or literally removing rainy texture from images).
Want an example?.Check out the below image taken from this paper: Using GANs for Security The rise of artificial intelligence has been wonderful for most industries.
But there’s a real concern that has shadowed the entire AI revolution – cyber threats.
Even deep neural networks are susceptible to being hacked.
A constant concern of industrial applications is that they should be robust to cyber attacks.
There’s a lot of confidential information on the line!.GANs are proving to be of immense help here, directly addressing the concern of “adversarial attacks”.
These adversarial attacks use a variety of techniques to fool deep learning architectures.
GANs are used to make existing deep learning models more robust to these techniques.
How?.By creating more such fake examples and training the model to identify them.
Pretty clever stuff.
A technique called SSGAN is used to do steganalysis of images and detect harmful encodings which shouldn’t have been there.
Generating Data with GANs Who among us wouldn’t love to collect more data for building our deep learning model? The availability of data in certain domains is a necessity, especially in domains where training data is needed to model supervideepeeop learning algorithms.
The healthcare industry comes to mind here.
GANs shine again as they can be used to generate synthetic data for supervision.
That’s right!. More details