Imagine, you have a dataset containing pictures of (example only, just to explain the task) cats and dogs. The data set is labeled, so we can train using supervised learning algorithms.
My goal is to make a cat from a dog. How to do it? For now, I have a couple of ideas which I can share:
Use a convolutional autoencoder and train on cats, then give a picture of a dog and see the result (I suppose, it will show the most "similar" cat, so the goal is reached)
Use an algorithm like GAN to transfer "style". I have no idea whether it is possible or not, but looks like a working idea
Which approaches could you recommend to try out?