In this paper, we tackle the problem of blind image super-resolution (SR) with a reformulated
degradation model and two novel modules. Following the common practices of blind SR, our …

Synthetic high-resolution (HR)\& low-resolution (LR) pairs are widely used in existing super-
resolution (SR) methods. To avoid the domain gap between synthetic and test images, most …

Although current deep learning-based methods have gained promising performance in the
blind single image super-resolution (SISR) task, most of them mainly focus on heuristically …

Degradation models play an important role in Blind super-resolution (SR). The classical
degradation model, which mainly involves blur degradation, is too simple to simulate real …

The asymmetric dual-lens configuration is commonly available on mobile devices
nowadays, which naturally stores a pair of wide-angle and telephoto images of the same …

Recent advancements in light field super-resolution (SR) have yielded impressive results. In
practice, however, many existing methods are limited by assuming fixed degradation …

In Taiwan, traditional production equipment for the mainframe panels is imported from
overseas, and the parameters are adjusted through the operation panel for automated …

To achieve promising results on blind image super-resolution (SR), some attempts
leveraged the low resolution (LR) images to predict the kernel and improve the SR …

In recent years, with the increase in the depth and width of convolutional neural networks,
single image super-resolution (SISR) algorithms have made significant breakthroughs in …

Deep learning-based methods have achieved significant successes on solving the blind
super-resolution (BSR) problem. However most of them request supervised pre-training on …