Image restoration is a critical task in low-level computer vision, aiming to restore high-quality
images from degraded inputs. Various models, such as convolutional neural networks …

Existing face super-resolution methods depend on deep convolutional networks (DCN) to
recover high-quality reconstructed images. They either acquire information in a single space …

Taking photos of digital screens often produces color-distorting moire patterns caused by
inconsistency between the color filter array of cameras and the sub-pixel layout of screens …

Existing infrared and visible image fusion methods suffer from edge information loss, artifact
introduction, and image distortion. Therefore, a dual-branch network model based on the …

Watching low resolution standard dynamic range (LR SDR) video on a 4K high dynamic
range (HDR) TV is not the best viewing experience. Joint super-resolution (SR) and SDRTV …

Landslide detection is crucial for natural disaster risk management. Deep-learning-based
object-detection algorithms have been shown to be effective in landslide studies. However …

Self-supervised denoising frameworks have recently been proposed to learn denoising
models without noisy-clean image pairs, showing great potential in various applications. The …

Printed photographs can be easily warped, wrinkled, and even deteriorated over time.
Existing methods treat the restoration of scratches as a pure inpainting problem that neglects …

Manga is a fashionable Japanese-style comic form that is composed of black-and-white
strokes and is generally displayed as raster images on digital devices. Typical mangas have …

Recent Transformer-based networks have shown impressive performance on single image
denoising tasks. While the Transformer model promotes the interaction of long-range …