Temporal sentence grounding in videos (TSGV), aka, natural language video localization
(NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that …

As an increasingly popular task in multimedia information retrieval, video moment retrieval
(VMR) aims to localize the target moment from an untrimmed video according to a given …

Due to the strong nonlinear representation capabilities of deep neural networks and the low
storage and high efficiency characteristics of hash learning, deep cross-modal hashing has …

Video moment retrieval aims to retrieve a target moment from an untrimmed video that
semantically corresponds to the given language query. Existing methods commonly treat it …

Video anomaly detection (VAD) has been paid increasing attention due to its potential
applications, its current dominant tasks focus on online detecting anomalies, which can be …

This article studies the multimedia problem of temporal sentence grounding (TSG), which
aims to accurately determine the specific video segment in an untrimmed video according to …

The Weakly-Supervised Audio-Visual Video Parsing (AVVP) task aims to parse a video into
temporal segments and predict their event categories in terms of modalities, labeling them …

Given an untrimmed video and a text query, Video Moment Retrieval (VMR) aims at
retrieving a specific moment where the video content is semantically related to the text …

Text-based video retrieval is a well-studied task aimed at retrieving relevant videos from a
large collection in response to a given text query. Most existing TVR works assume that …

To improve remote sensing image transmission efficiency, we propose a cloud detection
method using a multi-feature embedded learning support vector machine (SVM) to address …