Video Summary

Video summarization aims to condense lengthy videos into shorter, informative representations, preserving key events and information. Current research focuses on developing efficient algorithms, often employing graph-based representations, transformer networks, and generative adversarial networks (GANs), to achieve this, with a growing emphasis on incorporating both visual and audio cues, even across multiple modalities like text and video. These advancements are improving accessibility to large video datasets and enhancing applications in diverse fields, such as education, surveillance, and content analysis.