In single image deblurring, the``coarse-to-fine''scheme, ie gradually restoring the sharp
image on different resolutions in a pyramid, is very successful in both traditional optimization …

Due to the spatially variant blur caused by camera shake and object motions under different
scene depths, deblurring images captured from dynamic scenes is challenging. Although …

Because of the internal malfunction of satellite sensors and poor atmospheric conditions
such as thick cloud, the acquired remote sensing data often suffer from missing information …

In this paper, we present an effective and efficient face deblurring algorithm by exploiting
semantic cues via deep convolutional neural networks (CNNs). As face images are highly …

Blind image deblurring, ie, deblurring without knowledge of the blur kernel, is a highly ill-
posed problem. The problem can be solved in two parts: 1) estimate a blur kernel from the …

We present an effective blind image deblurring method based on a data-driven
discriminative prior. Our work is motivated by the fact that a good image prior should favor …

This paper studies the problem of blind face restoration from an unconstrained blurry, noisy,
low-resolution, or compressed image (ie, degraded observation). For better recovery of fine …

We present a method to extract a video sequence from a single motion-blurred image.
Motion-blurred images are the result of an averaging process, where instant frames are …

Single-image super-resolution is a fundamental task for vision applications to enhance the
image quality with respect to spatial resolution. If the input image contains degraded pixels …

In this paper, we present an end-to-end deblurring network designed specifically for a class
of data. Unlike the prior supervised deep-learning works that extensively rely on large sets of …