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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 Aufrufe • vor 3 Jahren •via X (Twitter)

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6 Kommentare

Profilbild von Matthias Niessner

Matthias Niessnervor 3 Jahren

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.

Profilbild von Michael Black

Michael Blackvor 3 Jahren

@CasualEffects Cool idea.

Profilbild von Efstratios Gavves

Efstratios Gavvesvor 3 Jahren

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

Profilbild von Ruoshi Liu

Ruoshi Liuvor 3 Jahren

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

Profilbild von 田中義弘 | taziku CEO / AI × Creative

田中義弘 | taziku CEO / AI × Creativevor 3 Jahren

Potential technologies. Thanks for the info!

Profilbild von Tianyu He

Tianyu Hevor 3 Jahren

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

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