Due to the attenuation and scattering of light by water, there are many quality defects in raw
underwater images such as color casts, decreased visibility, reduced contrast, et al.. Many …

We propose a no-reference image quality assessment (NR-IQA) approach that learns from
rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese …

Blind or no-reference video quality assessment of user-generated content (UGC) has
become a trending, challenging, heretofore unsolved problem. Accurate and efficient video …

Existing blind image quality assessment (BIQA) methods are mostly opinion-aware. They
learn regression models from training images with associated human subjective scores to …

Blind image quality assessment (BIQA) research aims to develop a perceptual model to
evaluate the quality of distorted images automatically and accurately without access to the …

An important aim of research on the blind image quality assessment (IQA) problem is to
devise perceptual models that can predict the quality of distorted images with as little prior …

We propose a natural scene statistic-based distortion-generic blind/no-reference (NR)
image quality assessment (IQA) model that operates in the spatial domain. The new model …

Numerous single image super-resolution (SISR) algorithms have been proposed during the
past years to reconstruct a high-resolution (HR) image from its low-resolution (LR) …

In this paper we propose a new no-reference (NR) image quality assessment (IQA) metric
using the recently revealed free-energy-based brain theory and classical human visual …

To improve the viewer's Quality of Experience (QoE) and optimize computer graphics
applications, 3D model quality assessment (3D-QA) has become an important task in the …