With the rapid growth of video data, video summarization is a promising approach to shorten
a lengthy video into a compact version. Although supervised summarization approaches …

In this paper we present our work on improving the efficiency of adversarial training for
unsupervised video summarization. Our starting point is the SUM-GAN model, which creates …

Audio and vision are two main modalities in video data. Multimodal learning, especially for
audiovisual learning, has drawn considerable attention recently, which can boost the …

There is an abundance of digital video content due to the cloud's phenomenal growth and
security footage; it is therefore essential to summarize these videos in data centers. This …

The current landscape of research leveraging large language models (LLMs) is
experiencing a surge. Many works harness the powerful reasoning capabilities of these …

To automatically produce a brief yet expressive summary of a long video, an automatic
algorithm should start by resembling the human process of summary generation. Prior work …

It is difficult to detect roll marks on hot-rolled steel plates as they have a low contrast in the
images. A periodical defect detection method based on a convolutional neural network …

The high redundancy among keyframes is a critical issue for the prior summarizing methods
in dealing with user-created videos. To address the critical issue, we present a Graph …

The goal of video summarization is to automatically shorten videos such that it conveys the
overall story without losing relevant information. In many application scenarios, improper …

Sentiment analysis has broad application prospects in the field of social opinion mining. The
openness and invisibility of the internet makes users' expression styles more diverse and …