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 …

In an underwater scene, wavelength-dependent light absorption and scattering degrade the
visibility of images, causing low contrast and distorted color casts. To address this problem …

Underwater images play an essential role in acquiring and understanding underwater
information. High-quality underwater images can guarantee the reliability of underwater …

In real-world scenarios, many factors may harm face recognition performance, eg., large
pose, bad illumination, low resolution, blur and noise. To address these challenges …

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 …

Human faces are one interesting object class with numerous applications. While significant
progress has been made in the generic deblurring problem, existing methods are less …

Poisson distribution is used for modeling noise in photon-limited imaging. While canonical
examples include relatively exotic types of sensing like spectral imaging or astronomy, the …

The increasing demand for high image quality in mobile devices brings forth the need for
better computational enhancement techniques, and image denoising in particular. To this …

In this paper, we propose an effective and efficient face deblurring algorithm by exploiting
semantic cues via deep convolutional neural networks. As the human faces are highly …

In this paper, we tackle depth estimation and blur removal from a single out-of-focus image.
Previously, depth is estimated, and blurred is removed using multiple images; for example …