3 accepted papers
Existing image super-resolution (SR) methods often cause oversharpening, especially in defocus images. However, we found that defocus regions and focus regions have different levels of difficulty in recovery. This provides an opportunity for efficient enhancements. In this paper, we propose DefocusS…
In this paper, we propose a novel Enhanced Self-mined Text Guided Super-resolution Network (ESTGN) for single image super-resolution (SISR). Unlike preceding methods, ESTGN autonomously mines task-related text from images and uses it to guide SR for high-frequency detail restoration. The proposed me…
A key problem in blind image quality assessment (BIQA) is how to effectively model the properties of human visual system in a data-driven manner. In this paper, we propose a simple and efficient BIQA model based on a novel framework which consists of a fully convolutional neural network (FCNN) and a…