Unlike natural image deblurring, which primarily prioritizes perceptual quality, Quick Response (QR) code deblurring aims to ensure successful decoding. QR codes are characterized by highly structured patterns with sharp edges, which provide strong structural priors for restoration. However, existing deep learning methods rarely exploit these priors explicitly. To address this limitation, we propose the Edge-Guided Attention Block (EGAB), which incorporates explicit edge priors into a Transforme