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--- |
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tags: |
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- model_hub_mixin |
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- pytorch_model_hub_mixin |
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license: cc-by-nc-4.0 |
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language: |
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- en |
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pipeline_tag: image-to-3d |
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--- |
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<div align="center"> |
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<h1>VGGT: Visual Geometry Grounded Transformer</h1> |
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<a href="https://jytime.github.io/data/VGGT_CVPR25.pdf" target="_blank" rel="noopener noreferrer"> |
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<img src="https://img.shields.io/badge/Paper-VGGT" alt="Paper PDF"> |
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</a> |
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<a href="https://arxiv.org/abs/2503.11651"><img src="https://img.shields.io/badge/arXiv-2503.11651-b31b1b" alt="arXiv"></a> |
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<a href="https://vgg-t.github.io/"><img src="https://img.shields.io/badge/Project_Page-green" alt="Project Page"></a> |
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<a href='https://huggingface.co/spaces/facebook/vggt'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Demo-blue'></a> |
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**[Meta AI Research](https://ai.facebook.com/research/)**; **[University of Oxford, VGG](https://www.robots.ox.ac.uk/~vgg/)** |
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[Jianyuan Wang](https://jytime.github.io/), [Minghao Chen](https://silent-chen.github.io/), [Nikita Karaev](https://nikitakaraevv.github.io/), |
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[Andrea Vedaldi](https://www.robots.ox.ac.uk/~vedaldi/), [Christian Rupprecht](https://chrirupp.github.io/), [David Novotny](https://d-novotny.github.io/) |
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</div> |
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## Overview |
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Visual Geometry Grounded Transformer (VGGT, CVPR 2025) is a feed-forward neural network that directly infers all key 3D attributes of a scene, including extrinsic and intrinsic camera parameters, point maps, depth maps, and 3D point tracks, **from one, a few, or hundreds of its views, within seconds**. |
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## Quick Start |
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Please refer to our [Github Repo](https://github.com/facebookresearch/vggt) |
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## Citation |
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If you find our repository useful, please consider giving it a star ⭐ and citing our paper in your work: |
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```bibtex |
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@inproceedings{wang2025vggt, |
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title={VGGT: Visual Geometry Grounded Transformer}, |
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author={Wang, Jianyuan and Chen, Minghao and Karaev, Nikita and Vedaldi, Andrea and Rupprecht, Christian and Novotny, David}, |
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, |
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year={2025} |
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} |
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``` |
