Underwater images serve as crucial mediums for conveying marine information.
Nevertheless, due to the inherent complexity of the underwater environment, underwater …

The annotation of blind image quality assessment (BIQA) is labor-intensive and time-
consuming especially for authentic images. Training on synthetic data is expected to be …

Due to the diversity of assessment requirements in various application scenarios for the IQA
task, existing IQA methods struggle to directly adapt to these varied requirements after …

Image quality assessment (IQA) has always been a popular research topic. There have
been many methods proposed for predicting image quality, also known as the mean opinion …

In this paper, we propose a blind image quality assessment (BIQA) method using self-
attention and a recurrent neural network (RNN); this approach can effectively capture both …

Blind image quality assessment (BIQA) targets predict the perceptual quality of an image
without any reference information. However, known methods have considerable room for …

With the rapid growth of in-the-wild videos taken by non-specialists, blind video quality
assessment (VQA) has become a challenging and demanding problem. Although lots of …

Underwater enhanced images (UEIs) are affected by not only the color cast and haze effect
due to light attenuation and scattering, but also the over-enhancement and texture distortion …

Faithful measurement of perceptual quality is of significant importance to various multimedia
applications. By fully utilizing reference images, full-reference image quality assessment (FR …

In this paper, a framework based on two feature extraction networks and a multilevel feature
fusion (MFF) network is proposed. Multilevel degradation features can be obtained through …