We propose a new model for no-reference video quality assessment (VQA). Our approach
uses a new idea of highly-localized space-time (ST) slices called Space-Time Chips (ST …

We propose a new prototype model for no-reference video quality assessment (VQA) based
on the natural statistics of space-time chips of videos. Space-time chips (ST-chips) are a …

There has recently been a great deal of interest in the development of algorithms that
objectively measure the integrity of video signals. Since video signals are being delivered to …

It is an important task to design models for universal no-reference video quality assessment
(NR-VQA) in multiple video processing and computer vision applications. However, most …

Video quality assessment (VQA) has received remarkable attention recently. Most of the
popular VQA models employ recurrent neural networks (RNNs) to capture the temporal …

Algorithms for video quality assessment (VQA) aim to estimate the qualities of videos in a
manner that agrees with human judgments of quality. Modern VQA algorithms often estimate …

We develop a full-reference (FR) video quality assessment framework that integrates
analysis of space–time slices (STSs) with frame-based image quality measurement (IQA) to …

Video quality assessment (VQA) exploits important properties of the sophisticated human
visual system (HVS). In this paper, we study a series of fundamental HVS characteristics for …

No-Reference (NR) video quality assessment (VQA) models are gaining popularity as they
offer scope for broader applicability to user-uploaded video-centric services such as …

The increased resolution of real-world videos presents a dilemma between efficiency and
accuracy for deep Video Quality Assessment (VQA). On the one hand, keeping the original …