Loading video...

Video Failed to Load

Go Home

1-layer, 8-bits parameter neural net doing pattern completion with sparse distributed activations and grid-cell-like vector fields can learn to retopo, maybe. #b3d #blender #retopology

22,379 views • 3 years ago •via X (Twitter)

7 Comments

Jeacom's profile picture
Jeacom3 years ago

Still having trouble with the brush coordinates thing.

Daniel Kreuter's profile picture
Daniel Kreuter3 years ago

I love this idea! I’m looking forward to seeing what will become this concept 😊

L̟̹̩̾̐apisSea🔶's profile picture
L̟̹̩̾̐apisSea🔶3 years ago

In my experience retopology is not really an issue of how to place the next quad in a grid, it's more an issue of how to achieve the wanted edge flow and density in certain area while minimizing poles or triangles and maximizing the preserved detail of the base shape.

Jeacom's profile picture
Jeacom3 years ago

well, this is gonna be a quad brush and not a auto-retopo button so unfortunately, solving poles is a task for the user. but I guess automatically placing and connecting dozens of quads in sensible locations with a single brush stroke is going to release a bit of the burden.

AFX's profile picture
AFX3 years ago

This looks awesome 👏

ADecadeAtMost's profile picture
ADecadeAtMost3 years ago

How’s Blender sending and receiving data to the model and whete is the model running?

Jeacom's profile picture
Jeacom3 years ago

The model is running on CPU locally inside blender's thread. its all mostly custom un-optmized python code and some Cython for vector crunching.

Related Videos