huggingface / huggingface/diffusers

Support MV-Adapter for multi-view generation

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contributions-welcome New pipeline/model
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Beschreibung

### Model/Pipeline/Scheduler description

[MV-Adapter](https://huanngzh.github.io/MV-Adapter-Page/) is a creative productivity tool that seamlessly transfer text-to-image models to multi-view generators.

Highlights:
- generate 768x768 multi-view images
- work well with personalized models, LCM, ControlNet
- support text or image to multi-view (reconstruct 3D thereafter), or with geometry guidance for 3D texture generation
- arbitrary view generation

Btw, I can help implement it in `diffusers`. But I am not sure whether it should be implemented in the `diffusers` kernel like `t2i_adapter` and `ip_adapter`, or in community pipelines.

### Open source status

- [X] The model implementation is available.
- [X] The model weights are available (Only relevant if addition is not a scheduler).

### Provide useful links for the implementation

Official implementation: https://github.com/huanngzh/MV-Adapter
Model weights: https://huggingface.co/huanngzh/mv-adapter

Beitragsleitfaden

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Rechercherichtung

Start by reading the official MV-Adapter implementation and comparing the existing t2i_adapter and ip_adapter integrations in diffusers. Determine whether the model belongs in the diffusers kernel or a community pipeline, then verify support for the linked model weights and the multi-view generation capabilities described in the issue.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
python, pytorch
Bereich
machine-learning
Issue-Typ
Feature
Schwierigkeit
5/5
Geschätzter Aufwand
Über eine Woche
Aktivitätsstatus
Veraltet
Klarheit
Größtenteils klar
Anfängerfreundlichkeit
25/100

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