Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …

Process of information extraction (IE) is used to extract useful information from unstructured
or semi-structured data. Big data arise new challenges for IE techniques with the rapid …

Abstract Video Temporal Grounding (VTG), which aims to ground target clips from videos
(such as consecutive intervals or disjoint shots) according to custom language queries (eg …

Video-language pre-training (VLP) has become increasingly important due to its ability to
generalize to various vision and language tasks. However, existing egocentric VLP …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Video summarization technologies aim to create a concise and complete synopsis by
selecting the most informative parts of the video content. Several approaches have been …

The goal of multimodal summarization is to extract the most important information from
different modalities to form summaries. Unlike unimodal summarization, the multimodal …

A generic video summary is an abridged version of a video that conveys the whole story and
features the most important scenes. Yet the importance of scenes in a video is often …

Video summarization aims to facilitate large-scale video browsing by producing short,
concise summaries that are diverse and representative of original videos. In this paper, we …

This paper addresses the problem of unsupervised video summarization, formulated as
selecting a sparse subset of video frames that optimally represent the input video. Our key …