README.md

---
library_name: diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
tags:
  - corradapter
  - mvadapter
  - image-to-multiview
  - multiview-generation
  - stable-diffusion-xl
---

# CorrAdapter-Model-on-MVAdapter

This model repository contains the trained **MVAdapter + CorrAdapter*** checkpoint for image-conditioned static multi-view generation from the CorrAdapter project.

CorrAdapter* is the trained variant of CorrAdapter on top of MV-Adapter image-to-multiview SDXL. The checkpoint is saved in Hugging Face sharded PyTorch format:

```text
pytorch_model.bin.index.json
pytorch_model-00001-of-00004.bin
pytorch_model-00002-of-00004.bin
pytorch_model-00003-of-00004.bin
pytorch_model-00004-of-00004.bin
```

This is not a standalone Diffusers pipeline. Use it with the CorrAdapter MVAdapter subproject.

## Usage

From the CorrAdapter MVAdapter directory:

```bash
python -m scripts.inference_i2mv_sdxl \
  --adapter_path SuhZhang/CorrAdapter-Model-on-MVAdapter \
  --adapter_weight_name pytorch_model.bin.index.json \
  --image assets/demo/i2mv/A_decorative_figurine_of_a_young_anime-style_girl.png \
  --text "A decorative figurine of a young anime-style girl" \
  --seed 21 \
  --output outputs/demo_i2mv_trained/output.png \
  --remove_bg
```

For local loading, replace `--adapter_path` with the local model directory path.

## Expected Code

The loader in `mvadapter/loaders/custom_adapter.py` supports `pytorch_model.bin.index.json` and loads only the keys needed by the MVAdapter CorrAdapter pipeline. The inference script also accepts:

```bash
--adapter_weight_name auto
```

when the directory contains `pytorch_model.bin.index.json`.

## Citation

```bibtex
@InProceedings{Zhang_2026_CVPR,
  author = {Zhang, Shihua and Shen, Qiuhong and Wang, Xinchao},
  title = {Align Images Before You Generate},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2026},
  pages = {30521-30531}
}
```

Please also cite MV-Adapter when using this checkpoint.