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 …

Where previous reviews on content-based image retrieval emphasize what can be seen in
an image to bridge the semantic gap, this survey considers what people tag about an image …

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

Social image tag refinement, which aims to improve tag quality by automatically completing
the missing tags and rectifying the noise-corrupted ones, is an essential component for …

In this article, we exploit the problem of annotating a large-scale image corpus by label
propagation over noisily tagged web images. To annotate the images more accurately, we …

In this paper, we present a multi-label sparse coding framework for feature extraction and
classification within the context of automatic image annotation. First, each image is encoded …

In this paper, we exploit the problem of inferring images' semantic concepts from community-
contributed images and their associated noisy tags. To infer the concepts more accurately …

With the proliferation of Web 2.0 applications, user-supplied social tags are commonly
available in social media as a means to bridge the semantic gap. On the other hand, the …

Automatic image annotation (AIA) plays a vital role in dealing with the exponentially growing
digital images. Image annotation helps in effective retrieval, organization, classification, auto …

Large-scale user contributed images with tags are easily available on photo sharing
websites. However, the noisy or incomplete correspondence between the images and tags …