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Can we apply diffusion directly on MLP weights? Yes!!! We show generalization to new 3D shapes and 4D mesh animations: "HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion" #ICCV2023! Project: Video:

Matthias Niessner

48,486 subscribers

86,046 views • 3 years ago •via X (Twitter)

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6 Comments

Matthias Niessner3 years ago

Quite interesting that neural fields can be directly used as representations for generative models. One open question is what MLP weight structure works best for generalization. Super cool work by @ErkocZiya in collaboration with @angelaqdai, @fangchangma, and Qi Shan.

Michael Black3 years ago

@CasualEffects Cool idea.

Efstratios Gavves3 years ago

We had a similar idea in our brainstorming sessions, curious to read in detail. Sounds excellent!!

Ruoshi Liu3 years ago

Very cool work! How does it compare with MeshDiffusion whose geometric representation is more explicit?

田中義弘 | taziku CEO / AI × Creative3 years ago

Potential technologies. Thanks for the info!

Tianyu He3 years ago

One question: why not generate triplane representation? since it more straightforward for diffusion models.

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46,151 views • 3 years ago