Super-resolution (SR) is an essential class of low-level vision tasks, which aims to improve
the resolution of images or videos in computer vision. In recent years, significant progress …

Exposure correction task aims to correct the underexposure and its adverse overexposure
images to the normal exposure in a single network. As well recognized, the optimization flow …

Lightness adaptation is vital to the success of image processing to avoid unexpected visual
deterioration, which covers multiple aspects, eg, low-light image enhancement, image …

Several recent studies advocate the use of spectral discriminators, which evaluate the
Fourier spectra of images for generative modeling. However, the effectiveness of the …

Deep learning-based source dehazing methods trained on synthetic datasets have
achieved remarkable performance but suffer from dramatic performance degradation on real …

The high-resolution screen of edge devices stimulates a strong demand for efficient image
super-resolution (SR). An emerging research, SR-LUT, responds to this demand by …

Existing methods have demonstrated effective performance on a single degradation type. In
practical applications, however, the degradation is often unknown, and the mismatch …

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 …

Image fusion aims to generate a high-quality image from multiple images captured under
varying conditions. The key problem of this task is to preserve complementary information …

Adverse weather conditions significantly impact the machine vision perception of unmanned
platforms such as drones and autonomous vehicles. Therefore, restoring and enhancing …