# LAM: Official Pytorch Implementation
English | 中文
[](https://aigc3d.github.io/projects/LAM/)
[](https://arxiv.org/pdf/2502.17796)
[](https://huggingface.co/spaces/3DAIGC/LAM)
[](https://www.modelscope.cn/studios/Damo_XR_Lab/LAM_Large_Avatar_Model)
[](https://www.apache.org/licenses/LICENSE-2.0)
### LAM: Large Avatar Model for One-shot Animatable Gaussian Head
#### SIGGRAPH 2025
##### Yisheng He*, Xiaodong Gu*, Xiaodan Ye, Chao Xu, Zhengyi Zhao, Yuan Dong†, Weihao Yuan†, Zilong Dong, Liefeng Bo
##### Tongyi Lab, Alibaba Group
#### **"Build 3D Interactive Chatting Avatar with One Image in Seconds!"**
## 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**
## 📢 News
**[April 30, 2026]** We have released the technical report and project page of [MeshLAM](https://arxiv.org/abs/2604.22865v1), CVPR 2026!
**[September 9, 2025]** We have released the technical report of [PanoLAM](https://arxiv.org/pdf/2509.07552)!
**[May 20, 2025]** We have released the [WebGL-Render](https://github.com/aigc3d/LAM_WebRender)!
**[May 10, 2025]** The [ModelScope](https://www.modelscope.cn/studios/Damo_XR_Lab/LAM_Large_Avatar_Model) 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](tools/AVATAR_EXPORT_GUIDE.md) that allows users to chat with any LAM-generated 3D digital humans on OpenAvatarChat. 🔥
**[April 21, 2025]** We have released the WebGL Interactive Chatting Avatar SDK on [OpenAvatarChat](https://github.com/HumanAIGC-Engineering/OpenAvatarChat) (including LLM, ASR, TTS, Avatar), with which you can freely chat with the 3D Digital Human generated by LAM ! 🔥
**[April 19, 2025]** We have released the [Audio2Expression](https://github.com/aigc3d/LAM_Audio2Expression) model, which can animate the generated LAM Avatar with audio input ! 🔥
### 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](https://github.com/HumanAIGC-Engineering/OpenAvatarChat), including LLM, ASR, TTS, Avatar.
## 🚀 Get Started
### Online Demo
Avatar Generation from One Image:
[](https://huggingface.co/spaces/3DAIGC/LAM)
[](https://www.modelscope.cn/studios/Damo_XR_Lab/LAM_Large_Avatar_Model)
Interactive Chatting:
[](https://huggingface.co/spaces/HumanAIGC-Engineering-Team/open-avatar-chat)
[](https://www.modelscope.cn/studios/HumanAIGC-Engineering/open-avatar-chat)
### Environment Setup
We provide a one-click installation package on Windows (Cuda 12.8), supported by "十字鱼".
[Video](https://www.bilibili.com/video/BV13QGizqEey)
[Download Link](https://virutalbuy-public.oss-cn-hangzhou.aliyuncs.com/share/aigc3d/data/LAM/Installation/LAM-windows-one-click-install.zip)
#### Linux:
```bash
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](scripts/install/WINDOWS_INSTALL.md).
### 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](https://huggingface.co/3DAIGC/LAM-20K) | [Link](https://www.modelscope.cn/models/Damo_XR_Lab/LAM-20K/summary) | 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
```bash
# 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
```bash
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
```bash
python app_lam.py
```
If you want to export ZIP files for real-time conversations on OpenAvatarChat, please refer to the [Guide](tools/AVATAR_EXPORT_GUIDE.md).
```bash
python app_lam.py --blender_path /path/blender
```
### Inference
```bash
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](https://github.com/3DTopia/OpenLRM)
- [GAGAvatar](https://github.com/xg-chu/GAGAvatar)
- [GaussianAvatars](https://github.com/ShenhanQian/GaussianAvatars)
- [VHAP](https://github.com/ShenhanQian/VHAP)
Thanks for their excellent works and great contribution.
### More Works
Welcome to follow our other interesting works:
- [LHM](https://github.com/aigc3d/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}
}
```