Current artificially distorted image quality assessment (IQA) databases are small in size and
limited in content. Larger IQA databases that are diverse in content could benefit the …

The ability to estimate the perceptual error between images is an important problem in
computer vision with many applications. Although it has been studied extensively, however …

Traditional full-reference image quality assessment (IQA) metrics generally predict the
quality of the distorted image by measuring its deviation from a perfect quality image called …

A key problem in blind image quality assessment (BIQA) is how to effectively model the
properties of human visual system in a data-driven manner. In this paper, we propose a …

The Structural Similarity (SSIM) Index is a very widely used image/video quality model that
continues to play an important role in the perceptual evaluation of compression algorithms …

Blind image quality assessment (BIQA) methods aim to predict quality of images as
perceived by humans without access to a reference image. Recently, deep learning …

With the rapid proliferation of virtual reality (VR) technologies, the usage of VR in
multimedia, education, and social media platforms has increased due to realistic and …

We propose a method to estimate the mechanical parameters of fabrics using a casual
capture setup with a depth camera. Our approach enables to create mechanically‐correct …

Deep Neural Networks (DNNs) have been extensively used in many areas including image
processing, medical diagnostics and autonomous driving. However, DNNs can exhibit …

Multi-level deep-features have been driving state-of-the-art methods for aesthetics and
image quality assessment (IQA). However, most IQA benchmarks are comprised of artificially …