Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing
the resolution of low-resolution (LR) face images to generate high-resolution face images, is …

Video super-resolution (SR) is focused on reconstructing high-resolution frames from
consecutive low-resolution (LR) frames. Most previous video SR methods based on …

Deep convolutional neural networks (CNNs) have contributed to the significant progress of
the single-image super-resolution (SISR) field. However, the majority of existing CNN-based …

Face super-resolution reconstruction is the process of predicting high-resolution face
images from one or more observed low-resolution face images, which is a typical …

Image super-resolution (SR) techniques improve various remote sensing applications by
allowing for finer spatial details than those captured by the original acquisition sensors …

Cross-resolution face recognition (CRFR), which is important in intelligent surveillance and
biometric forensics, refers to the problem of matching a low-resolution (LR) probe face …

Although deep learning-based face recognition techniques have achieved amazing
performance in recent years, low-resolution (LR) face recognition remains challenging. In …

Face super-resolution (SR) has become an indispensable function in security solutions such
as video surveillance and identification system, but the distortion in facial components is a …

Image super-resolution (SR) is a fundamental technique in the field of image processing and
computer vision. Recently, deep learning has witnessed remarkable progress in many super …

To make the face hallucination process robust to impulse noise, a new outlier elimination
based iterative neighbor representation (OEINR) algorithm is proposed in this work. The …