Authors:
Toqa Alaa
1
;
Ahmad Mongy
1
;
Assem Bakr
1
;
Mariam Diab
1
and
Walid Gomaa
2
;
1
Affiliations:
1
Department of Computer Science and Engineering, Egypt-Japan University of Science and Technology, Alexandria, Egypt
;
2
Faculty of Engineering, Alexandria University, Alexandria, Egypt
Keyword(s):
Keyframe Selection, Event-Based Summarization, Supervised Methods, Unsupervised Methods, Attention Mechanism, Multi-Modal Learning, Generative Adversarial Networks.
Abstract:
The rapid expansion of video content across various industries, including social media, education, entertainment, and surveillance, has made video summarization an essential field of study. This survey aims to explore the latest techniques and approaches developed for video summarization, with a focus on identifying their strengths and drawbacks to guide future improvements. Key strategies such as reinforcement learning, attention mechanisms, generative adversarial networks, and multi-modal learning are examined in detail, along with their real-world applications and challenges. The paper also covers the datasets commonly used to benchmark these techniques, providing a comprehensive understanding of the current state and future directions of video summarization research.