A wacky idea

Let me start this by saying this will probably never happen lol. (I also have very very little experience with programming, let alone neural networks, so if this sounds dumb than that is probably why.)

I was thinking about how tedious remeshing is and some way to make it easier. Somehow I started thinking about AI assisted remeshing and I can’t stop thinking about it. Feed the AI a non-remeshed version of a model in the form of an obj text file or some equivalent and just let it do its thing. A remeshed version of the model could be used as the training data to compare the neural network’s results to.

If someone out there smarter than me wanted to try this that’d be cool.

The tricky part is how to properly present the data for the NN and how to get results back,

I don’t think feeding all the vertices edges and faces directly will work.

For a neural network, you would feed it a large library of sculpts and example retopo results done by hand for starters.

Though you’d still have other challenges, such as how to minimize memory consumption, minimize compute time, and minimizing the chance of the algorithm spazzing out if fed a mesh that deviates a bit from its training data (while avoiding the introduction of a problem known as ‘overfitting’).

The neural-based algorithms that have the best results (as of right now) allows you to feed in other data to help guide the algorithm, so you might have a sort of ‘shape’ pass that identifies common shapes such as ones that are cylindrical, conical, spherical, and cubic.

There was a discussion about this a while back, and this post (below) was a pretty good analysis on the subject: