LAM: Official Pytorch Implementation

<p align="center"> <strong>English | <a href="README_CN.md">中文</a></strong> </p>

<p align="center"> <img src="./assets/images/logo.jpeg" width="20%"> </p>

<p align="center"> LAM: Large Avatar Model for One-shot Animatable Gaussian Head </p>

<p align="center"> SIGGRAPH 2025 </p>

<p align="center"> Yisheng He*, Xiaodong Gu*, Xiaodan Ye, Chao Xu, Zhengyi Zhao, Yuan Dong†, Weihao Yuan†, Zilong Dong, Liefeng Bo </p>

<p align="center"> Tongyi Lab, Alibaba Group</p>

<p align="center"> "Build 3D Interactive Chatting Avatar with One Image in Seconds!" </p>

<p align="center"> <img src="./assets/images/teaser.jpg" width="100%"> </p>

Core Highlights 🔥🔥🔥

• Ultra-realistic 3D Avatar Creation from One Image in Seconds
• Super-fast Cross-platform Animating and Rendering on Any Devices
• Low-latency SDK for Realtime Interactive Chatting Avatar

<div align="center"> <video controls src="https://github.com/user-attachments/assets/98f66655-e1c1-40a9-ab58-bdd49dafedda" width="80%"> </video> </div>

📢 News

[September 9, 2025] We have released the technical report of PanoLAM!

[May 20, 2025] We have released the WebGL-Render!

[May 10, 2025] The ModelScope Demo now supports directly exporting the generated Avatar to files required by OpenAvatarChat for interactive chatting!

[April 30, 2025] We have released a Avatar Export Feature that allows users to chat with any LAM-generated 3D digital humans on OpenAvatarChat. 🔥 <br>

[April 21, 2025] We have released the WebGL Interactive Chatting Avatar SDK on OpenAvatarChat (including LLM, ASR, TTS, Avatar), with which you can freely chat with the 3D Digital Human generated by LAM ! 🔥 <br>

[April 19, 2025] We have released the Audio2Expression model, which can animate the generated LAM Avatar with audio input ! 🔥 <br>

<!-- **[April 10, 2025]** We have released the demo on [ModelScope](https://www.modelscope.cn/studios/Damo_XR_Lab/LAM_Large_Avatar_Model) Space ! <br> -->

To do list

• [x] Release LAM-small trained on VFHQ and Nersemble.
• [x] Release Huggingface space.
• [x] Release Modelscope space.
• [ ] Release LAM-large trained on a self-constructed large dataset.
• [x] Release WebGL Render for cross-platform animation and rendering.
• [x] Release audio driven model: Audio2Expression.
• [x] Release Interactive Chatting Avatar SDK with OpenAvatarChat, including LLM, ASR, TTS, Avatar.

🚀 Get Started

Online Demo

Avatar Generation from One Image:

Interactive Chatting:

Environment Setup

We provide a one-click installation package on Windows (Cuda 12.8), supported by "十字鱼".     Video     Download Link

Linux:

git clone https://github.com/aigc3d/LAM.git
cd LAM
# Install with Cuda 12.1
sh ./scripts/install/install_cu121.sh
# Or Install with Cuda 11.8
sh ./scripts/install/install_cu118.sh

Windows:

For Windows, please refer to the Windows Install Guide.

Model Weights

| Model | Training Data | HuggingFace | ModelScope | Reconstruction Time | A100 (A & R) | XiaoMi 14 Phone (A & R) | |---------|--------------------------------|----------|----------|---------------------|-----------------------------|-----------| | LAM-20K | VFHQ | TBD | TBD | 1.4 s | 562.9FPS | 110+FPS | | LAM-20K | VFHQ + NeRSemble | Link | Link | 1.4 s | 562.9FPS | 110+FPS | | LAM-20K | Our large dataset | TBD | TBD | 1.4 s | 562.9FPS | 110+FPS |

(A & R: Animating & Rendering )

HuggingFace Download

# Download Assets
huggingface-cli download 3DAIGC/LAM-assets --local-dir ./tmp
tar -xf ./tmp/LAM_assets.tar && rm ./tmp/LAM_assets.tar
tar -xf ./tmp/thirdparty_models.tar && rm -r ./tmp/
# Download Model Weights
huggingface-cli download 3DAIGC/LAM-20K --local-dir ./model_zoo/lam_models/releases/lam/lam-20k/step_045500/

ModelScope Download

pip3 install modelscope
# Download Assets
modelscope download --model "Damo_XR_Lab/LAM-assets" --local_dir "./tmp/"
tar -xf ./tmp/LAM_assets.tar && rm ./tmp/LAM_assets.tar
tar -xf ./tmp/thirdparty_models.tar && rm -r ./tmp/
# Download Model Weights
modelscope download "Damo_XR_Lab/LAM-20K" --local_dir "./model_zoo/lam_models/releases/lam/lam-20k/step_045500/"

Gradio Run

python app_lam.py

If you want to export ZIP files for real-time conversations on OpenAvatarChat, please refer to the Guide.

python app_lam.py --blender_path /path/blender

Inference

sh ./scripts/inference.sh ${CONFIG} ${MODEL_NAME} ${IMAGE_PATH_OR_FOLDER} ${MOTION_SEQ}

Acknowledgement

This work is built on many amazing research works and open-source projects:

• OpenLRM
• GAGAvatar
• GaussianAvatars
• VHAP

Thanks for their excellent works and great contribution.

More Works

Welcome to follow our other interesting works:

• LHM

Citation

@inproceedings{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},
  booktitle={Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers},
  pages={1--13},
  year={2025}
}