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 …

In recent years, cross-modal retrieval has drawn much attention due to the rapid growth of
multimodal data. It takes one type of data as the query to retrieve relevant data of another …

This paper introduces a powerful channel augmented joint learning strategy for the visible-
infrared recognition problem. For data augmentation, most existing methods directly adopt …

A complete defect detection task aims to achieve the specific class and precise location of
each defect in an image, which makes it still challenging for applying this task in practice …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

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 …

Matching person images between the daytime visible modality and night-time infrared
modality (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Existing …

Recently, multi-view representation learning has become a rapidly growing direction in
machine learning and data mining areas. This paper introduces two categories for multi …