让人脸二维码既美观又可扫，还能认出人脸
Face2QR: A Unified Framework for Aesthetic, Face-Preserving, and Scannable QR Code Generation
- 用统一扩散模型融合人脸与背景风格
- 重排二维码模块，保留人脸特征且不损识别率
- 优化潜在编码，提升扫描鲁棒性，适合社交场景
现有生成美观二维码的方法在融入人脸身份时，往往牺牲视觉美感或可扫描性。为此，我们提出Face2QR——一种统一框架，能和谐融合美学、人脸身份与可扫描性。其创新包含三部分：首先，ID-refined QR integration（IDQR）通过基于Stable Diffusion的统一框架与控制网络，无缝融合背景风格与人脸身份；其次，ID-aware QR ReShuffle（IDRS）有效解决人脸与二维码图案的冲突，重新排列二维码模块，在不破坏人脸完整性的同时保持可扫描性；最后，ID-preserved Scannability Enhancement（IDSE）通过潜在码优化显著提升扫描鲁棒性，实现人脸身份、美学质量与二维码功能的平衡。大量实验表明，该方法在保留人脸识别特征方面优于现有技术。代码已公开于该链接。
原文摘要 · Abstract (English)
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 Stable Diffusion (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. Codes are available at $\href{https://github.com/cavosamir/Face2QR}{\text{this URL link}}$.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。