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 …

In this paper, we study how to make unsupervised cross-modal hashing (CMH) benefit from
contrastive learning (CL) by overcoming two challenges. To be exact, i) to address the …

With the explosive growth of multimedia contents, multimedia retrieval is facing
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …

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 …

Person Re-identification (re-ID) has great potential to contribute to video surveillance that
automatically searches and identifies people across different cameras. Heterogeneous …

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 cross-modal search which aims to map multiple modality features into binary
codes has attracted increasingly attention due to its storage and search efficiency especially …

Cross-modal hashing aims to map heterogeneous multimedia data into a common
Hamming space, which can realize fast and flexible retrieval across different modalities …

Binary code learning has been emerging topic in large-scale cross-modality retrieval
recently. It aims to map features from multiple modalities into a common Hamming space …

Hyperspectral image superresolution is a highly attractive topic in computer vision and has
attracted many researchers' attention. However, nearly all the existing methods assume that …