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- <p align="center">
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- <h3 align="center"><strong>ShapeLLM-omni: A Native Multimodal LLM for 3D Generation and Understanding</strong></h3>
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- <p align="center">
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- <a href="https://jamesyjl.github.io/">Junliang Ye</a><sup>1,2*</sup>,
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- <a href="https://thuwzy.github.io/">Zhengyi Wang</a><sup>1,2*</sup>,
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- <a href="https://zhaorw02.github.io/">Ruowen Zhao</a><sup>1*</sup>,
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- <a href="">Shenghao Xie</a><sup>3</sup>,
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- <a href="https://ml.cs.tsinghua.edu.cn/~jun/index.shtml">Jun Zhu</a><sup>1,2†</sup>
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- <br>
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- <sup>*</sup>Equal Contribution.
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- <br>
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- <sup>†</sup>Corresponding authors.
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- <br>
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- <sup>1</sup>Tsinghua University,
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- <sup>2</sup>ShengShu,
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- <sup>3</sup>Peking University,
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- </p>
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- <div align="center">
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- <a href='https://arxiv.org/abs/2503.15265'><img src='https://img.shields.io/badge/arXiv-2503.15265-b31b1b.svg'></a> &nbsp;&nbsp;&nbsp;&nbsp;
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- <a href='https://jamesyjl.github.io/ShapeLLM/'><img src='https://img.shields.io/badge/Project-Page-Green'></a> &nbsp;&nbsp;&nbsp;&nbsp;
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- <a><img src='https://img.shields.io/badge/License-MIT-blue'></a> &nbsp;&nbsp;&nbsp;&nbsp;
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- <a href="https://huggingface.co/zzzrw/DeepMesh/tree/main"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Weights-HF-orange"></a> &nbsp;&nbsp;&nbsp;&nbsp;
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- <a href='https://www.youtube.com/watch?v=6grL7bSbQ2w'><img src='https://img.shields.io/badge/Youtube-Video-b31b1b.svg'>
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- </div>
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- ## Release
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- - [6/03] 🔥🔥We released the pretrained weights for both **ShapeLLM-omni** (7B) and **3DVQVAE**.
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- - [6/03] 🔥🔥We released 50k high-quality 3D edited data pairs.
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-
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- ## Important Notes
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- - Please refer to our [project_page](https://zhaorw02.github.io/DeepMesh/) for more examples.
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- ## Todo
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- - [ ] Release of training code.
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- - [ ] Release of model weights featuring multi-turn dialogue and 3D editing capabilities.
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- - [ ] Release of the entire 3D-Alpaca dataset.
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-
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- ## Acknowledgement
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- Our code is based on these wonderful repos:
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- * **[LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)**
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- * **[TRELLIS](https://github.com/microsoft/TRELLIS)**
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- * **[PointLLM](https://github.com/OpenRobotLab/PointLLM)**
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- * **[Qwen2.5-VL](https://github.com/QwenLM/Qwen2.5-VL)**
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- * [LLaMA-Mesh](https://github.com/nv-tlabs/LLaMA-Mesh)
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