--- 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 - **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 - **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 ![Demo Visuals](demo_visuals.gif) ## Citation **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} } ```