Video highlight detection is a task to automatically select the most engaging moments from a
long video. This problem is highly challenging since it aims to learn a general way of finding …

Video summarization, with the target to detect valuable segments given untrimmed videos, is
a meaningful yet understudied topic. Previous methods primarily consider inter-frame and …

In the last decade, the supply of online video content exploded. Automatic video
summarization has become necessary to allow content consumers to briefly glance at the …

The apparent" black box" nature of neural networks is a barrier to adoption in applications
where explainability is essential. This paper presents TAME (Trainable Attention Mechanism …

In this paper, we present a new process for creating video summaries in an unsupervised
manner. Our approach involves training a transformer encoder model to reconstruct missing …

Video summarization aims to generate a concise representation of a video capturing its
essential content and key moments while reducing its overall length. Although several …

We propose a graph-based representation learning framework for video summarization.
First we convert an input video to a graph where nodes correspond to each of the video …

Video summarization deals with the generation of a condensed version of the original video
by including meaningful frames or segments while eliminating redundant information. The …

Multimodal summarisation with multimodal output is drawing increasing attention due to the
rapid growth of multimedia data. While several methods have been proposed to summarise …

Our work examines the way in which large language models can be used for robotic
planning and sampling in the context of automated photographic documentation …