Here’s some ideas for assignments:
- As per usual, read through the papers and make sure you understand them
- Download and train a model using the full imagenet 1000k dataset
- Try improving one of your extra generative models by adding WGAN on top of it
- Use WGAN to create a generative model from any earlier paper, such as colorization, 3d view changing, noise removal, depth prediction, etc
In addition, next week we’ll be taking a look at mean shift clustering. So if you’re interested, see if you can implement it yourself in tensorflow or pytorch.
Post below with any questions, comments, or ideas.