Perceptual quality assessment plays a vital role in the visual communication systems owing
to the existence of quality degradations introduced in various stages of visual signal …

Explosive growth of data in digital world leads to the requirement of efficient technique to
store and transmit data. Due to limited resources, data compression (DC) techniques are …

Downsampling operations such as max pooling or strided convolution are ubiquitously
utilized in Convolutional Neural Networks (CNNs) to aggregate local features, enlarge …

In this paper, we propose an image quality transformer (IQT) that successfully applies a
transformer architecture to a perceptual full-reference image quality assessment (IQA) task …

Image quality assessment (IQA) algorithm aims to quantify the human perception of image
quality. Unfortunately, there is a performance drop when assessing the distortion images …

The performance of objective image quality assessment (IQA) models has been evaluated
primarily by comparing model predictions to human quality judgments. Perceptual datasets …

Traditional blind image quality assessment (IQA) measures generally predict quality from a
sole distorted image directly. In this paper, we first introduce multiple pseudo reference …

Image quality assessment (IQA) is the key factor for the fast development of image
restoration (IR) algorithms. The most recent IR methods based on Generative Adversarial …

Point cloud is emerged as a promising media format to represent realistic 3D objects or
scenes in applications, such as virtual reality, teleportation, etc. How to accurately quantify …

Perceptual image quality assessment (IQA) aims to use computational models to measure
the image quality in consistent with subjective evaluations. Visual saliency (VS) has been …