ML Deformer H20

Simulation can be used to obtain deformations that look more realistic than linear blend skinning. However, linear blend skinning is much faster. Can we learn from simulated poses to improve on linear blend skinning? This Machine Learning example shows how linear blend skinning can be improved on by learning from random poses.

This setup uses a TOP network to control all the stages of the Machine Learning: data generation, preprocessing and training. It demonstrates the use of several new Houdini 20 features that support ML, including the new ONNX SOP, the new Principal Component Analysis SOP, the new ROP Geometry Raw Output SOP, and enhancements to the Python Script TOP.

(1 response)


  • salar_td 8 months, 1 week ago  | 


  • wnschnapp 6 months ago  | 

    Hi There,

    Is Cappi included in this project? When I open the project, it seems like certain geometry are not linked. Are the remaining files available with the Hip file download? Thanks!

  • Rob Chapman 3 months, 3 weeks ago  | 

    looking forward to more info on this and how it connects with Unreal Engines ML deformer solution for realtime playback

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