Perceptual video quality assessment plays a vital role in the field of video processing due to
the existence of quality degradations introduced in various stages of video signal …

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 …

Measuring the perception of visual content is a long-standing problem in computer vision.
Many mathematical models have been developed to evaluate the look or quality of an …

Convolutional Neural Networks (CNN) and Graph Neural Networks (GNN), such as Graph
Attention Networks (GAT), are two classic neural network models, which are applied to the …

Image Quality Assessment (IQA) is a fundamental task in computer vision that has witnessed
remarkable progress with deep neural networks. Inspired by the characteristics of the human …

We present an approach to mitigating the risks of malicious image editing posed by large
diffusion models. The key idea is to immunize images so as to make them resistant to …

This paper outlines an end-to-end optimized lossy image compression framework using
diffusion generative models. The approach relies on the transform coding paradigm, where …

Visual anomaly detection addresses the problem of classification or localization of regions in
an image that deviate from their normal appearance. A popular approach trains an auto …

Objective measures of image quality generally operate by comparing pixels of a “degraded”
image to those of the original. Relative to human observers, these measures are overly …

Haze-free images are the prerequisites of many vision systems and algorithms, and thus
single image dehazing is of paramount importance in computer vision. In this field, prior …