In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …

Existing video hash functions are built on three isolated stages: frame pooling, relaxed
learning, and binarization, which have not adequately explored the temporal order of video …

The most striking successes in image retrieval using deep hashing have mostly involved
discriminative models, which require labels. In this paper, we use binary generative …

In recent years a vast amount of visual content has been generated and shared from various
fields, such as social media platforms, medical images, and robotics. This abundance of …

In this work, by re-examining the “matching” nature of Anomaly Detection (AD), we propose
a novel AD framework that simultaneously enjoys new records of AD accuracy and …

Hashing has attracted increasing research attention in recent years due to its high efficiency
of computation and storage in image retrieval. Recent works have demonstrated the …

Cross-modal retrieval, eg, using an image query to search related text and vice-versa, has
become a highlighted research topic, to provide flexible retrieval experience across multi …

For the multi-label image retrieval, the existing hashing algorithms neglect the dependency
between objects and thus fail to capture the attention information in the feature extraction …

Recently, deep Hamming hashing methods have been proposed for Hamming space
retrieval which enables constant-time search by hash table lookups instead of linear scan …

Hashing algorithm has been widely used to speed up image retrieval due to its compact
binary code and fast distance calculation. The combination with deep learning boosts the …