Q-Art Code: Generating Scanning-robust Art-style QR Codes by Deformable Convolution

Quick Response (QR) code is a popular form of matrix barcodes that are widely used to tag online links on print media (e.g., posters, leaflets, and books). However, standard QR codes typically appear as noise-like black/white squares (named modules) which seriously disrupt the attractiveness of their carriers. In this paper, we propose StyleCode-Net, a method to generate novel art-style QR codes which can better match the entire style of their carriers to improve the visual quality. For endowing QR codes with artistic elements, a big challenge is that the scanning-robustness must be preserved after transforming colors and textures. To address these issues, we propose a module-based deformable convolutional mechanism (MDCM) and a dynamic target mechanism (DTM) in StyleCode-Net. MDCM can extract the features of black and white modules of QR codes respectively. Then, the extracted features are fed to DTM to balance the scanning-robustness and the style representation. Extensive subjective and objective experiments show that our art-style QR codes have reached the state-of-the-art level in both visual quality and scanning-robustness, and these codes have the potential to replace standard QR codes in real-world applications.