DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement
Author: Jia-Wei Liao, Winston Wang, Tzu-Sian Wang, Li-Xuan Peng, Ju-Hsian Weng, Cheng-Fu Chou, Jun-Cheng Chen
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025
This repository implements a two-stage iterative refinement pipeline that leverages a pretrained ControlNet to generate aesthetic QR codes. Check out the project page here.
To set up the virtual environment and install the required packages, use the following commands:
virtualenv --python=python3.10 diffqrcoder
source diffqrcoder/bin/activate
pip install -r requirements.txt
To generate the aesthetic qrcode, run the following:
python generate_qrcode.py \
--controlnet_ckpt <checkpoint of controlnet> \
--pipe_ckpt <checkpoint of pipeline> \
--conditional_image_path <path of qrcode image> \
--output_folder <folder of generated image> \
--neg_prompt <negative prompt> \
--num_inference_steps <number of inference step> \
--qrcode_image_module_size <qrcode image module size> \
--qrcode_image_padding <qrcode image padding> \
-srg <scanning robust guidance scale> \
-pg <perceptual guidance scale>
If you use this code, please cite the following:
@inproceedings{liao2024diffqrcoder,
title = {DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement},
author = {Jia-Wei Liao, Winston Wang, Tzu-Sian Wang, Li-Xuan Peng, Ju-Hsian Weng, Cheng-Fu Chou, Jun-Cheng Chen},
booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
year = {2025},
}