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license: other
library_name: diffusers
pipeline_tag: image-to-image
base_model: stabilityai/sd-turbo
tags:
- image-restoration
- novel-view-synthesis
- 3d-gaussian-splatting
- dualdiff3d
---
# DualDiff
Official DualDiff repair checkpoint for
[DualDiff3D](https://github.com/Akaneqwq/DualDiff3D).
DualDiff repairs a degraded novel-view rendering using its structure together
with the appearance of a nearby reference image.
## Usage
The DualDiff3D code downloads this checkpoint automatically:
```bash
python -m DualDiff.hub
```
Run image-pair inference:
```bash
python DualDiff/infer.py \
--input_image /path/to/degraded_render.png \
--ref_image /path/to/reference.png \
--output_dir outputs/repair
```
The checkpoint contains the complete structure and appearance U-Net state
dictionaries plus the trained VAE LoRA and skip-connection parameters. It does
not contain optimizer state. The SD-Turbo VAE, text encoder, tokenizer,
scheduler, and base configuration are loaded separately by the code.
## Citation
```bibtex
@inproceedings{wang2026dualdiff3d,
title = {DualDiff3D: Dual Structure-Appearance Diffusion
Priors for Reliability-Enhanced 3D Gaussian Splatting},
author = {Qian Wang and Yu Wang and Weiqi Li and Xinhua Cheng
and Xiandong Meng and Ronggang Wang and Jian Zhang},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2026}
}
```
## License
The DualDiff code is released under Apache-2.0. This checkpoint is derived from
[SD-Turbo](https://huggingface.co/stabilityai/sd-turbo); use of the checkpoint
is also subject to the applicable SD-Turbo model license.
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