The past recent years have witnessed the explosive growth of image and video data on the Internet, which brings significant challenges and profound impacts to search and related technologies. It is challenging for many existing algorithms to effectively and efficiently handle very large collections of image and video contents, especially when the scale rises from tens of thousands to tens of millions or even billions. Fortunately, along with the growth of imagery contents, more and more resources on the Internet become available, such as the associated metadata, context and social information. In addition, the power of grassroots has been fully demonstrated in the Web 2.0 era. For example, they can easily tag and comment on millions of images and videos, as well as label millions of images via a simple game. These facts have both raised challenges of large-scale search and provided opportunities for inventing new methodologies and pushing forward the frontiers of information technology. Recently, many research efforts are dedicated to developing new search technologies to overcome the scalability issue. This trend of rapidly increasing data scales is anticipated to spread across a still wider range of research communities. This special issue is intended to bring together the latest research results in this direction. Scope The scope of this special issue is to cover all aspects that relate to large-scale image and video search. Topics of interest include, but are not limited to y Large-scale image and video indexing, including high-dimensional indexing, semantic-based indexing, etc. y Large-scale image and video copy detection and near-duplication detection. y Large-scale social-network analysis for image and video applications.