Abstract Evaluation of noise content or distortions present in an image is same as assessing
the quality of an image. Measurement of such quality index is challenging in the absence of …

We introduce a new large-scale dataset that links the assessment of image quality issues to
two practical vision tasks: image captioning and visual question answering. First, we identify …

Over the last two decades, there has been a surge of interest in the research of image
quality assessment due to its wide applicability to many domains. In general, the aim of …

Blind image quality assessment (BIQA) aims to predict perceptual image quality scores
without access to reference images. State-of-the-art BIQA methods typically require subjects …

It is widely known that the wavelet coefficients of natural scenes possess certain statistical
regularities which can be affected by the presence of distortions. The DIIVINE (Distortion …

Designing a logo for a new brand is a lengthy and tedious back-and-forth process between
a designer and a client. In this paper we explore to what extent machine learning can solve …

As the image enhancement algorithms developed in recent years, how to compare the
performances of different image enhancement algorithms becomes a novel task. In this …

Multimedia, including audio, image, and video, etc., is a ubiquitous part of modern life.
Quality evaluation, both objective and subjective, is of fundamental importance for various …

Image quality assessment (IQA) is in great demand for high quality image selection in the
big data era. The challenge of reduced-reference (RR) IQA is how to use limited data to …

Previously, no-reference (NR) stereoscopic 3D (S3D) image quality assessment (IQA)
algorithms have been limited to the extraction of reliable hand-crafted features based on an …