Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …

Semantic communications has received growing interest since it can remarkably reduce the
amount of data to be transmitted without missing critical information. Most existing works …

Semantic Communication (SC) has emerged as a novel communication paradigm that
provides a receiver with meaningful information extracted from the source to maximize …

At present, and increasingly so in the future, much of the captured visual content will not be
seen by humans. Instead, it will be used for automated machine vision analytics and may …

Abstract Image Coding for Machines (ICM) aims to compress images for AI tasks analysis
rather than meeting human perception. Learning a kind of feature that is both general (for AI …

Most video compression methods aim to improve the decoded video visual quality, instead
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …

Recent works on learned image compression perform encoding and decoding processes in
a full-resolution manner, resulting in two problems when deployed for practical applications …

In recent years, video data has dominated internet traffic and becomes one of the major data
formats. With the emerging 5G and internet of things (IoT) technologies, more and more …

Almost all digital videos are coded into compact representations before being transmitted.
Such compact representations need to be decoded back to pixels before being displayed to …

Advances in both lossy image compression and semantic content understanding have been
greatly fueled by deep learning techniques, yet these two tasks have been developed …