Hashing has been widely investigated for large-scale image retrieval due to its search
effectiveness and computation efficiency. In this work, we propose a novel Semantic Guided …

Hashing methods have been extensively applied to efficient multimedia data indexing and
retrieval on account of the explosion of multimedia data. Cross-modal hashing usually …

Due to storage and search efficiency, hashing has become significantly prevalent for nearest
neighbor search. Particularly, deep hashing methods have greatly improved the search …

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 …

With the development of video network, image set classification (ISC) has received a lot of
attention and can be used for various practical applications, such as video based …

Hashing could significantly accelerate large-scale image search by transforming the high-
dimensional features into binary Hamming space, where efficient similarity search can be …

Hashing is becoming increasingly popular for approximate nearest neighbor searching in
massive databases due to its storage and search efficiency. Recent supervised hashing …

Hashing plays a pivotal role in nearest-neighbor searching for large-scale image retrieval.
Recently, deep learning-based hashing methods have achieved promising performance …

Hashing has recently sparked a great revolution in cross-modal retrieval because of its low
storage cost and high query speed. Recent cross-modal hashing methods often learn …

This paper proposes a deep hashing framework, namely, unsupervised deep video hashing
(UDVH), for large-scale video similarity search with the aim to learn compact yet effective …