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

Due to the continuous booming of surveillance and Web videos, video moment localization,
as an important branch of video content analysis, has attracted wide attention from both …

The deep hashing based retrieval method is widely adopted in large-scale image and video
retrieval. However, there is little investigation on its security. In this paper, we propose a …

Most existing unsupervised video hashing methods are built on unidirectional models with
less reliable training objectives, which underuse the correlations among frames and the …

With the current exponential growth of video-based social networks, video retrieval using
natural language is receiving ever-increasing attention. Most existing approaches tackle this …

Most metric learning techniques typically focus on sample embedding learning, while
implicitly assume a homogeneous local neighborhood around each sample, based on the …

Unsupervised video hashing usually optimizes binary codes by learning to reconstruct input
videos. Such reconstruction constraint spends much effort on frame-level temporal context …

Deep hashing integrates the advantages of deep learning and hashing technology, and has
become the mainstream of the large-scale image retrieval field. However, when training the …

Abstract Self-Supervised Video Hashing (SSVH) models learn to generate short binary
representations for videos without ground-truth supervision, facilitating large-scale video …

In this paper, we address the problem of shot-level video summarization, which aims at
selecting a subset of video shots as a summary to represent the original video contents …