3DAIGC/LAM-20K

This model has been pushed to the Hub using the PytorchModelHubMixin integration:

• —Library: [More Information Needed]
• —Docs: [More Information Needed]

license: apache-2.0

• —en --- <div align="center"> <h1>LAM: Large Avatar Model for One-shot Animatable Gaussian Head</h1>

<div align="center" style="display: flex; justify-content: center; flex-wrap: wrap;"> <!-- <a href='LICENSE'><img src='https://img.shields.io/badge/license-MIT-yellow'></a> --> <a href='https://arxiv.org/pdf/2502.17796'><img src='https://img.shields.io/badge/📜-arXiv:2503-10625'></a> <a href='https://aigc3d.github.io/projects/LAM/'><img src='https://img.shields.io/badge/🌐-ProjectWebsite-blueviolet'></a> <a href='https://huggingface.co/spaces/3DAIGC/LAM'><img src='https://img.shields.io/badge/🤗-HuggingFaceSpace-blue'></a> <a href="https://www.apache.org/licenses/LICENSE-2.0"><img src="https://img.shields.io/badge/📃-Apache--2.0-929292"></a> </div> </div>

Overview

This repository contains the models of the paper LAM.

LAM creates animatable Gaussian heads with one-shot images in a single forward pass in seconds. The reconstructed Gaussian avatar can be reenacted and rendered on various platforms in real-time.

Quick Start

Please refer to our Github Repo

Download Model

from huggingface_hub import snapshot_download 
# LAM-20K Model
model_dir = snapshot_download(repo_id='3DAIGC/LAM-20K', cache_dir='./pretrained_models/huggingface/')

Citation

@article{he2025lam,
  title={LAM: Large Avatar Model for One-shot Animatable Gaussian Head},
  author={He, Yisheng and Gu, Xiaodong and Ye, Xiaodan and Xu, Chao and Zhao, Zhengyi and Dong, Yuan and Yuan, Weihao and Dong, Zilong and Bo, Liefeng},
  journal={arXiv preprint arXiv:2502.17796},
  year={2025}
}