@inproceedings{
cui2024faceqr,
title={Face2{QR}: A Unified Framework for Aesthetic, Face-Preserving, and Scannable {QR} Code Generation},
author={Xuehao Cui and Guangyang Wu and Zhenghao Gan and Guangtao Zhai and Xiaohong Liu},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=rvBabL7DUu}
}
Existing methods to generate aesthetic QR codes, such as image and style transfer techniques, tend to compromise either the visual appeal or the scannability of QR codes when they incorporate human face identity. Addressing these imperfections, we present Face2QR—a novel pipeline specifically designed for generating personalized QR codes that harmoniously blend aesthetics, face identity, and scannability. Our pipeline introduces three innovative components. First, the ID-refined QR integration (IDQR) seamlessly intertwines the background styling with face ID, utilizing a unified SD-based framework with control networks. Second, the ID-aware QR ReShuffle (IDRS) effectively rectifies the conflicts between face IDs and QR patterns, rearranging QR modules to maintain the integrity of facial features without compromising scannability. Lastly, the ID-preserved Scannability Enhancement (IDSE) markedly boosts scanning robustness through latent code optimization, striking a delicate balance between face ID, aesthetic quality and QR functionality. In comprehensive experiments, Face2QR demonstrates remarkable performance, outperforming existing approaches, particularly in preserving facial recognition features within custom QR code designs.
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation
Xuehao Cui Guangyang Wu Zhenghao Gan Guangtao Zhai Xiaohong Liu