AnimPortrait3D

This is the official code repository for our SIG'25 paper:

Text-based Animatable 3D Avatars with Morphable Model Alignment

ACM SIGGRAPH 2025 (Conference Track)

Yiqian Wu, Malte Prinzler, Xiaogang Jin*, Siyu Tang

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Requirements

1. Python 3.10
2. CUDA>=12.1
3. At least 24 GB of memory
4. Linux
5. Tested on NVIDIA TITAN RTX GPU (3.5h per portrait)

Installation

Clone AnimPortrait3D to /path/to/AnimPortrait3D

git clone git@github.com:oneThousand1000/AnimPortrait3D.git

Create environment

cd AnimPortrait3D
conda env create -f environment.yaml 
source activate AnimPortrait3D

Run Install Script

bash ./install.sh

Prepare Data

Run fetch_data.sh to download all required files. Before proceeding, ensure you have registered accounts for SMPLX, SMPL, and SMPLify, FLAME to access the necessary models.

Note: The script downloads pretrained diffusion models, ControlNet, and the Sapiens model to /path/to/pretrained_model. Please ensure that the specified path has sufficient storage space (> 50 GB).

bash ./fetch_data.sh \
    /path/to/pretrained_model \
    /path/to/AnimPortrait3D

# example:

bash ./fetch_data.sh \
    /path/to/AnimPortrait3D/pretrained_model \
    /path/to/AnimPortrait3D

AnimPortrait3D builds upon the outputs of Portrait3D as its starting point. To generate your own starting avatar, please refer to Portrait3D. Alternatively, you ca