Multi-view learning is an emerging direction in machine learning which considers learning
with multiple views to improve the generalization performance. Multi-view learning is also …

The aim of this paper is to give an overview of domain adaptation and transfer learning with
a specific view on visual applications. After a general motivation, we first position domain …

Subspace clustering is an effective method that has been successfully applied to many
applications. Here, we propose a novel subspace clustering model for multi-view data using …

Cross-modal retrieval aims to enable flexible retrieval across different modalities. The core
of cross-modal retrieval is how to measure the content similarity between different types of …

Person re-identification (Re-ID) is an important problem in video surveillance, aiming to
match pedestrian images across camera views. Currently, most works focus on RGB-based …

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 …

Domain adaptation is one of the most challenging tasks of modern data analytics. If the
adaptation is done correctly, models built on a specific data representation become more …

Given the benefits of its low storage requirements and high retrieval efficiency, hashing has
recently received increasing attention. In particular, cross-modal hashing has been widely …

Hashing based methods have attracted considerable attention for efficient cross-modal
retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to …

This paper proposes a method of gait recognition using a convolutional neural network
(CNN). Inspired by the great successes of CNNs in image recognition tasks, we feed in the …