Pixel-Guided Dual-Branch Attention Network for Joint Image Deblurring and Super-Resolution
Image deblurring and super-resolution (SR) are computer vision tasks aiming to restore image detail and spatial scale, respectively. Besides, only a few recent literatures contribute to this task, as conventional methods deal with SR or deblurring separately. We focus on designing a novel Pixel-Guided dual-branch attention network (PDAN) that handles both tasks jointly to address this issue. Then, we propose a novel loss function better focus on large and medium range errors. Extensive experiments demonstrated that the proposed PDAN with the novel loss function not only generates remarkably clear HR images and achieves compelling results for joint image deblurring and SR tasks. In addition, our method achieves second place in NTIRE 2021 Challenge on track 1 of Image Deblurring Challenge.