| --- |
| license: apache-2.0 |
| pipeline_tag: image-to-3d |
| --- |
| |
| # TriplaneGuassian Model Card |
|
|
| <div align="center"> |
|
|
| [**Project Page**](https://zouzx.github.io/TriplaneGaussian/) **|** [**Paper (ArXiv)**](https://arxiv.org/abs/2312.09147) **|** [**Code**](https://github.com/VAST-AI-Research/TriplaneGaussian) **|** [**Gradio demo**](https://huggingface.co/spaces/VAST-AI/TriplaneGaussian) |
| </div> |
|
|
| ## Introduction |
| TGS enables fast reconstruction from single-view image in a few seconds based on a hybrid Triplane-Gaussian 3D representation. |
|
|
| ## Examples |
|
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| ### Results on Images Generated by [Midjourney](https://www.midjourney.com/) |
|
|
| <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/644dbf6453ad80c6593bf748/BcJp8alZRXAIdPmfbVGdx.qt"></video> |
|
|
| ### Results on Captured Real-world Images |
|
|
| <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/644dbf6453ad80c6593bf748/bgAxqUQpnisQAmsGZ9Q_0.qt"></video> |
|
|
| ## Model Details |
| The model `model_lvis_rel.ckpt` is trained on Objaverse-LVIS dataset, which only includes ~45K synthetic objects. |
|
|
| ## Usage |
| You can directly download the model in this repository or employ the model in python script by: |
| ```python |
| from huggingface_hub import hf_hub_download |
| MODEL_CKPT_PATH = hf_hub_download(repo_id="VAST-AI/TriplaneGaussian", filename="model_lvis_rel.ckpt", repo_type="model") |
| ``` |
|
|
| More details can be found in our [Github repository](https://github.com/VAST-AI-Research/TriplaneGaussian). |
|
|
| ## Citation |
| If you find this work helpful, please consider citing our paper: |
| ```bibtex |
| @article{zou2023triplane, |
| title={Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers}, |
| author={Zou, Zi-Xin and Yu, Zhipeng and Guo, Yuan-Chen and Li, Yangguang and Liang, Ding and Cao, Yan-Pei and Zhang, Song-Hai}, |
| journal={arXiv preprint arXiv:2312.09147}, |
| year={2023} |
| } |
| ``` |
