Low-light images challenge both human perceptions and computer vision algorithms. It is
crucial to make algorithms robust to enlighten low-light images for computational …

Deep learning algorithms have recently achieved promising deraining performances on
both the natural and synthetic rainy datasets. As an essential low-level pre-processing …

Segmenting anatomical structures in medical images has been successfully addressed with
deep learning methods for a range of applications. However, this success is heavily …

Video frame interpolation (VFI) is a very active research topic due to its broad applicability to
many applications, including video enhancement, video encoding, and slow-motion effects …

Microscopy image analysis often requires the segmentation of objects, but training data for
this task is typically scarce and hard to obtain. Here we propose DenoiSeg, a new method …

In medical image segmentation, domain generalization poses a significant challenge due to
domain shifts caused by variations in data acquisition devices and other factors. These shifts …

Pixel-level image fusion is an effective way to fully exploit the rich texture information of
visible images and the salient target characteristics of infrared images. With the …

Blind video deblurring restores sharp frames from a blurry sequence without any prior. It is a
challenging task because the blur due to camera shake, object movement and defocusing is …

Deraining driven by semantic segmentation task is very important for autonomous driving
because rain streaks and raindrops on the car window will seriously degrade the …

Recently, stacked networks show powerful performance in Image Restoration, such as
challenging motion deblurring problems. However, the number of stacking levels is a hyper …