Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …

With the rapid development of information storage and networking technologies, quintillion
bytes of data are generated every day from social networks, business transactions, sensors …

Due to storage and search efficiency, hashing has become significantly prevalent for nearest
neighbor search. Particularly, deep hashing methods have greatly improved the search …

In this tutorial, we define and discuss key aspects of the problem of computational inference
of aesthetics and emotion from images. We begin with a background discussion on …

Nearest neighbor search is a fundamental problem in various research fields like machine
learning, data mining and pattern recognition. Recently, hashing-based approaches, for …

Many social image search engines are based on keyword/tag matching. This is because tag-
based image retrieval (TBIR) is not only efficient but also effective. The performance of TBIR …

In this paper, we review 300 references on video retrieval, indicating when text-only
solutions are unsatisfactory and showing the promising alternatives which are in majority …

We propose a deep hashing framework for sketch retrieval that, for the first time, works on a
multi-million scale human sketch dataset. Leveraging on this large dataset, we explore a few …

Along with the explosive growth of multimedia data, automatic multimedia tagging has
attracted great interest of various research communities, such as computer vision …

The Bag-of-Words (BoW) model is a promising image representation technique for image
categorization and annotation tasks. One critical limitation of existing BoW models is that …