PixelSmile/PixelSmile

PixelSmile: Toward Fine-Grained Facial Expression Editing

                   

📢 Updates

• [03/27/2026] 🔥 arXiv paper is now available.
• [03/26/2026] 🔥 Demo is live, give it a try 🎮
• [03/25/2026] 🔥 Inference Code and Benchmark Data are released.
• [03/24/2026] 🔥 Project Page and Model Weight (Preview) are released.

⚡ Quick Start

Quick start for PixelSmile inference.

1. Install the environment in Installation.
2. Download the base model and PixelSmile weights in Model Download.
3. Run inference in Inference.

🔧 Installation

Clone the repository and enter the project directory:

git clone https://github.com/Ammmob/PixelSmile.git
cd PixelSmile

Create and activate a clean conda environment:

conda create -n pixelsmile python=3.10
conda activate pixelsmile

Install the inference dependencies:

pip install -r requirements.txt

Patch the current diffusers installation for the Qwen image edit bug:

bash scripts/patch_qwen_diffusers.sh

🤗 Model Download

PixelSmile uses Qwen/Qwen-Image-Edit-2511 as the base model.

Model	Stage	Data Type	Download
PixelSmile-preview	Preview	Human	Hugging Face

✨ A more stable version is coming soon, with improved human expression editing performance and support for anime expression editing.

🎨 Inference

PixelSmile supports two simple ways to run inference.

Option 1. Edit the default arguments in the script

bash scripts/run_infer.sh

You can edit scripts/run_infer.sh and directly modify the default values in DEFAULT_ARGS.

Option 2. Pass arguments from the command line

bash scripts/run_infer.sh \
  --image-path /path/to/input.jpg \
  --output-dir /path/to/output \
  --model-path /path/to/Qwen-Image-Edit-2511 \
  --lora-path /path/to/PixelSmile.safetensors \
  --expression happy \
  --scales 0 0.5 1.0 1.5 \
  --seed 42

Command-line arguments will override the default values in the script.

📖 Citation

If you find PixelSmile useful in your research or applications, please consider citing our work.

@article{hua2026pixelsmile,
  title={PixelSmile: Toward Fine-Grained Facial Expression Editing},
  author={Jiabin Hua and Hengyuan Xu and Aojie Li and Wei Cheng and Gang Yu and Xingjun Ma and Yu-Gang Jiang},
  journal={arXiv preprint arXiv:2603.25728},
  year={2026}
}