FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers
- August 14, 2025: Our work is merged to ComfyUI-Wan ! Thank kijai for the update 👏!
- August 12, 2025: We released the inference code, model weights and datasets.
For more interesting results, please visit our website.
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Clone the repo:
git clone https://github.com/Fantasy-AMAP/fantasy-portrait.git
cd fantasy-portrait
Install dependencies:
apt-get install ffmpeg
# Ensure torch >= 2.0.0
pip install -r requirements.txt
# Note: flash attention must be installed
pip install flash_attn
We make public the first multi-portrait facial expression video dataset Multi-Expr Dataset, Please download it via the ModelScope or Huggingface.
Models | Download Link | Notes |
---|---|---|
Wan2.1-I2V-14B-720P | 🤗 Huggingface 🤖 ModelScope | Base model |
FantasyPortrait | 🤗 Huggingface 🤖 ModelScope | Our emo condition weights |
Download models using huggingface-cli:
pip install "huggingface_hub[cli]"
huggingface-cli download Wan-AI/Wan2.1-I2V-14B-720P --local-dir ./models/Wan2.1-I2V-14B-720P
huggingface-cli download acvlab/FantasyPortrait --local-dir ./models
Download models using modelscope-cli:
pip install modelscope
modelscope download Wan-AI/Wan2.1-I2V-14B-720P --local_dir ./models/Wan2.1-I2V-14B-720P
modelscope download amap_cvlab/FantasyPortrait --local_dir ./models
bash infer_single.sh
If you use input image and drive videos with multiple people, you can run as follows:
bash infer_multi.sh
If you use input image with multiple people and different multiple single-human driven videos, you can run as follows:
bash infer_multi_diff.sh
We present a detailed table here. The model is tested on a single A100.
torch_dtype |
num_persistent_param_in_dit |
Speed | Required VRAM |
---|---|---|---|
torch.bfloat16 | None (unlimited) | 15.5s/it | 40G |
torch.bfloat16 | 7*10**9 (7B) | 32.8s/it | 20G |
torch.bfloat16 | 0 | 42.6s/it | 5G |
We ❤️ contributions from the open-source community! If your work has improved FantasyPortrait, please inform us. Or you can directly e-mail frank.jf@alibaba-inc.com. We are happy to reference your project for everyone's convenience.
If you find this repository useful, please consider giving a star ⭐ and citation
@article{wang2025fantasyportrait,
title={FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers},
author={Wang, Qiang and Wang, Mengchao and Jiang, Fan and Fan, Yaqi and Qi, Yonggang and Xu, Mu},
journal={arXiv preprint arXiv:2507.12956},
year={2025}
}
Thanks to Wan2.1, PD-FGC and DiffSynth-Studio for open-sourcing their models and code, which provided valuable references and support for this project. Their contributions to the open-source community are truly appreciated.