Saltar al contenido
ModelPublicadoExterno
Descargar

MeshAnything

MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

TipoOtherVersiónRevision d023238Bcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
2,22 GB
Versión
vRevision d023238
Actualizado
15 sept 2026
Descargas
58
Fuente
Hugging Face

Extracto de la fuente

MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

Fuentes

1 fuente
Hugging FacePrincipalVersión d023238e47212c8800380ef008f4f7822824a705
huggingface.co/Yiwen-ntu/MeshAnything/tree/d023238e47212c8800380ef008f4f7822824a705

Verificado 1 sept

Artefactos del modelo

1 artefacto

MeshAnything_350m.pth

pth · 2,22 GB · SHA-256 f2de0cbd19d7…5f6b · Hugging Face

Download file

Extractos de fuentes

2 extractos

--- pipeline_tag: image-to-3d library_name: mesh-anything --- <p align="center"> <h3 align="center"><strong>MeshAnything:<br> Artist-Created Mesh Generation<br> with Autoregressive Transformers</strong></h3> <p align="center"> <a href="https://buaacyw.github.io/">Yiwen Chen</a><sup>1,2*</sup>, <a href="https://tonghe90.github.io/">Tong He</a><sup>2†</sup>, <a href="https://dihuang.me/">Di Huang</a><sup>2</sup>, <a href="https://ywcmaike.github.io/">Weicai Ye</a><sup>2</sup>, <a href="https://ch3cook-fdu.github.io/">Sijin Chen</a><sup>3</sup>, <a href="https://me.kiui.moe/">Jiaxiang Tang</a><sup>4</sup><br> <a href="https://chenxin.tech/">Xin Chen</a><sup>5</sup>, <a href="https://caizhongang.github.io/">Zhongang Cai</a><sup>6</sup>, <a href="https://scholar.google.com.hk/citations?user=jZH2IPYAAAAJ&hl=en">Lei Yang</a><sup>6</sup>, <a href="https://www.skicyyu.org/">Gang Yu</a><sup>7</sup>, <a href="https://guosheng.github.io/">Guosheng Lin</a><sup>1†</sup>, <a href="https://icoz69.github.io/">Chi Zhang</a><sup>8†</sup> <br> <sup>*</sup>Work done during a research internship at Shanghai AI Lab. <br> <sup>†</sup>Corresponding authors. <br> <sup>1</sup>S-Lab, Nanyang Technological University, <sup>2</sup>Shanghai AI Lab, <br> <sup>3</sup>Fudan University, <sup>4</sup>Peking University, <sup>5</sup>University of Chinese Academy of Sciences, <br> <sup>6</sup>SenseTime Research, <sup>7</sup>Stepfun, <sup>8</sup>Westlake University </p> ## Release - [6/17] 🔥🔥 We released the 350m version of **MeshAnything**. ## Contents - [Release](#release) - [Contents](#contents) - [Installation](#installation) - [Usage](#usage) - [Important Notes](#important-notes) - [TODO](#todo) - [Acknowledgement](#acknowledgement) - [BibTeX](#bibtex) ## Installation Our environment has been tested on Ubuntu 22, CUDA 11.8 with A100, A800 and A6000. 1. Clone our repo and create conda environment ``` git clone https://github.com/buaacyw/MeshAnything.git && cd MeshAnything conda create -n MeshAnything python==3.10.13 conda activate MeshAnything pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu118 pip install -r requirements.txt pip install flash-attn --no-build-isolation ``` ## Usage ### Local Gradio Demo <a href='https://github.com/gradio-app/gradio'><img src='https://img.shields.io/github/stars/...

Source context: 58 downloads · 14 likes · Pipeline image-to-3d · Library mesh-anything · Repo Yiwen-ntu/MeshAnything