With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …

The goal of sequential recommendation (SR) is to predict a user's potential interested items
based on her/his historical interaction sequences. Most existing sequential recommenders …

With the rapid development of science and technology, all types of mixed media contain
large amounts of data. Traditional single multimedia data can no longer satisfy daily …

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

Unsupervised cross-modal hashing (UCMH) has been commonly explored to support large-
scale cross-modal retrieval of unlabeled data. Despite promising progress, most existing …

Given a text query, partially relevant video retrieval (PRVR) seeks to find untrimmed videos
containing pertinent moments in a database. For PRVR, clip modeling is essential to capture …

With the efficiency of storage and retrieval speed, the hashing methods have attracted a lot
of attention for cross-modal retrieval applications. In contrast to traditional cross-modal …

Deep hashing technology, known for its low-cost storage and rapid retrieval, has become a
focal point in cross-modal retrieval research as multimodal data continue to grow. However …

With the rapid development of science and technology, all types of mixed media contain
large amounts of data. Traditional single multimedia data can no longer satisfy daily …