This chapter focuses on explainable video summarization, a technology that could significantly advance the content production workflow of Media organizations. It starts by presenting the current state of the art in the fields of deep-learning-based video summarization and explainable video analysis and understanding. Following, it focuses on video summarization methods that rely on the use of
... [Show full abstract] attention mechanisms and reports on previous works that investigated the use of attention for explaining the outcomes of deep neural networks. Subsequently, it briefly describes a state-of-the-art attention-based architecture for unsupervised video summarization and discusses a recent work that examines the use of various attention-based signals for explaining the outcomes of video summarization. Finally, it provides recommendations about future research directions.