Multimedia retrieval plays an indispensable role in big data utilization. Past efforts mainly
focused on single-media retrieval. However, the requirements of users are highly flexible …

Human beings experience life through a spectrum of modes such as vision, taste, hearing,
smell, and touch. These multiple modes are integrated for information processing in our …

Multimodal representation learning, which aims to narrow the heterogeneity gap among
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …

Matching images and sentences demands a fine understanding of both modalities. In this
article, we propose a new system to discriminatively embed the image and text to a shared …

This paper strives to find amidst a set of sentences the one best describing the content of a
given image or video. Different from existing works, which rely on a joint subspace for their …

Automatically describing the content of an image has been attracting considerable research
attention in the multimedia field. To represent the content of an image, many approaches …

Nowadays, cross-modal retrieval plays an important role to flexibly find useful information
across different modalities of data. Effectively measuring the similarity between different …

Recent artificial intelligence research has witnessed great interest in automatically
generating text descriptions of images, which are known as the image captioning task …

An ever increasing part of communication between persons involve the use of pictures, due
to the cheap availability of powerful cameras on smartphones, and the cheap availability of …

Cross-modal hashing maps heterogeneous multimedia data into a common Hamming
space to realize fast and flexible cross-modal retrieval. Supervised cross-modal hashing …