MV-Adapter Model Card
Project Page | Paper (ArXiv) | Paper (HF) | Code | Gradio demo
Create High-fidelity Multi-view Images with Various Base T2I Models and Various Conditions.
Introduction
MV-Adapter is a creative productivity tool that seamlessly transfer text-to-image models to multi-view generators.
Highlights:
- 768x768 multi-view images
- work well with personalized models (e.g. DreamShaper, Animagine), LCM, ControlNet
- support text or image to multi-view (reconstruct 3D thereafter), or with geometry guidance for 3D texture generation
- arbitrary view generation
Examples
Model Details
| Model | Base Model | HF Weights | Demo Link |
|---|---|---|---|
| Text-to-Multiview | SD2.1 | mvadapter_t2mv_sd21.safetensors | |
| Text-to-Multiview | SDXL | mvadapter_t2mv_sdxl.safetensors | General / Anime |
| Image-to-Multiview | SD2.1 | mvadapter_i2mv_sd21.safetensors | |
| Image-to-Multiview | SDXL | mvadapter_i2mv_sdxl.safetensors | Demo |
| Text-Geometry-to-Multiview | SDXL | mvadapter_tg2mv_sdxl.safetensors | |
| Image-Geometry-to-Multiview | SDXL | mvadapter_ig2mv_sdxl.safetensors | |
| Image-to-Arbitrary-Views | SDXL |
Usage
Refer to our Github repository.
Citation
If you find this work helpful, please consider citing our paper:
@article{huang2024mvadapter,
title={MV-Adapter: Multi-view Consistent Image Generation Made Easy},
author={Huang, Zehuan and Guo, Yuanchen and Wang, Haoran and Yi, Ran and Ma, Lizhuang and Cao, Yan-Pei and Sheng, Lu},
journal={arXiv preprint arXiv:2412.03632},
year={2024}
}