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---
license: other
license_name: snap-non-commercial-license
license_link: LICENSE
datasets:
- allenai/objaverse
language:
- en
pipeline_tag: image-to-3d
---
## Model Details
GTR is a large 3D reconstruction model that takes multi-view images as input and enables the generation of high-quality meshes with faithful texture reconstruction within seconds.
## Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [Snap Research](https://github.com/snap-research)
- **License:** [snap-non-commercial-license](https://huggingface.co/snap-research/gtr/blob/main/LICENSE)
## Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** [snap_gtr](https://github.com/snap-research/snap_gtr)
- **Paper:** [arxiv](https://arxiv.org/abs/2406.05649)
- **Web:** [project](https://snap-research.github.io/GTR/)
## How to Get Started with the Model
### Installation
We recommend using `Python>=3.10`, `PyTorch==2.7.0`, and `CUDA>=12.4`.
```bash
conda create --name gtr python=3.10
conda activate gtr
pip install -U pip
pip install torch==2.7.0 torchvision==0.22.0 torchmetrics==1.2.1 --index-url https://download.pytorch.org/whl/cu124
pip install -U xformers --index-url https://download.pytorch.org/whl/cu124
pip install -r requirements.txt
```
### How to Use
Please follow instructions [here](https://github.com/snap-research/snap_gtr/tree/main?tab=readme-ov-file#how-to-use).
## Demo

## Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
```bibtex
@article{zhuang2024gtr,
title={Gtr: Improving large 3d reconstruction models through geometry and texture refinement},
author={Zhuang, Peiye and Han, Songfang and Wang, Chaoyang and Siarohin, Aliaksandr and Zou, Jiaxu and Vasilkovsky, Michael and Shakhrai, Vladislav and Korolev, Sergey and Tulyakov, Sergey and Lee, Hsin-Ying},
journal={arXiv preprint arXiv:2406.05649},
year={2024}
}
```
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