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pipeline_tag: image-to-3d
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<div align="center">
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<h1>Streaming 4D Visual Geometry Transformer</h1>
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</div>
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### [Paper](https://arxiv.org/abs/2507.11539) | [Project Page](https://wzzheng.net/StreamVGGT)
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>Streaming 4D Visual Geometry Transformer
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>Dong Zhuo<sup>\*</sup>, [Wenzhao Zheng](https://wzzheng.net/)<sup>*</sup>$\dagger$, Jiahe Guo, Yuqi Wu, [Jie Zhou](https://scholar.google.com/citations?user=6a79aPwAAAAJ&hl=en&authuser=1), [Jiwen Lu](http://ivg.au.tsinghua.edu.cn/Jiwen_Lu/)
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<sup>*</sup> Equal contribution. $\dagger$ Project leader.
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**StreamVGGT**, a causal transformer architecture for **real-time streaming 4D visual geometry perception** compatiable with LLM-targeted attention mechanism (e.g., [FlashAttention](https://github.com/Dao-AILab/flash-attention)), delivers both fast inference and high-quality 4D reconstruction.
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## Overview
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Given a sequence of images, unlike offline models that require reprocessing the entire sequence and reconstructing the entire scene upon receiving each new image, our StreamVGGT employs temporal
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causal attention and leverages cached memory token to support efficient incremental on-the-fly reconstruction, enabling interative and real-time online applitions.
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## Quick start
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Please refer to our [Github Repo](https://github.com/wzzheng/StreamVGGT).
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## Citation
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If you find this project helpful, please consider citing the following paper:
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```
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@article{streamVGGT,
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title={Streaming 4D Visual Geometry Transformer},
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author={Dong Zhuo and Wenzhao Zheng and Jiahe Guo and Yuqi Wu and Jie Zhou and Jiwen Lu},
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journal={arXiv preprint arXiv:2507.11539},
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year={2025}
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}
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```
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