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 …

Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …

Approximate nearest neighbour search (ANNS) in high-dimensional space is an essential
and fundamental operation in many applications from many domains such as multimedia …

Unsupervised hashing is an important approach for large-scale content-based remote
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …

Deep hashing has been widely used in multimedia retrieval systems due to its storage and
computation efficiency. Unsupervised hashing has received a lot of attention in recent years …

Cross-modal hashing is an important approach for multimodal data management and
application. Existing unsupervised cross-modal hashing algorithms mainly rely on data …

Unsupervised semantic hashing has emerged as an indispensable technique for fast image
search, which aims to convert images into binary hash codes without relying on labels …

The majority of deep unsupervised hashing methods usually first construct pairwise
semantic similarity information and then learn to map images into compact hash codes while …

In this paper, we present a novel Two-stEp Cross-modal Hashing method, TECH for short,
for cross-modal retrieval tasks. As a two-step method, it first learns hash codes based on …

Hashing has received a lot of attention in large-scale image retrieval due to its high retrieval
accuracy and speed. Unsupervised deep hashing methods with pseudo-labels suffer from …