Text2QR: Achieving Aesthetic Customization and Scanning Robustness for QR Code Generation
Concepts de base
Text2QR aims to harmonize user-defined aesthetics and scanning robustness in QR code generation, surpassing previous methods.
Résumé
Text2QR introduces a pioneering approach to balance customization and scannability in QR codes. The QR Aesthetic Blueprint (QAB) module generates a blueprint image guiding the generation process, while the Scannability Enhancing Latent Refinement (SELR) process enhances scanning robustness. The method seamlessly integrates aesthetic appeal with practical utility, outperforming existing techniques. Experimental results demonstrate high success rates in scanning across various devices and readers. Additionally, Text2QR excels in aesthetic quality compared to other methods, as confirmed by user studies and benchmark metrics.
Text2QR
Stats
100% average success rates in scanning across different mobile devices and readers.
83.3% preference for Text2QR in a user study comparing different QR code generation methods.
AesBench score of 95.5 for Text2QR, indicating superior aesthetic quality compared to other methods.