Intelligent video summarization algorithms allow to quickly convey the most relevant
information in videos through the identification of the most essential and explanatory content …

This paper presents a new method for unsupervised video summarization. The proposed
architecture embeds an Actor-Critic model into a Generative Adversarial Network and …

The goal of video summarization is to distill a raw video into a more compact form without
losing much semantic information. However, previous methods mainly consider the diversity …

Although video summarization has achieved tremendous success benefiting from Recurrent
Neural Networks (RNN), RNN-based methods neglect the global dependencies and multi …

This paper studies the video summarization task by formulating it as a sequential decision-
making process, in which the input is a sequence of video frames and the output is a subset …

In this paper, we propose a multiscale hierarchical attention approach for supervised video
summarization. Different from most existing supervised methods which employ bidirectional …

With the rapid growth of video data, video summarization technique plays a key role in
reducing people's efforts to explore the content of videos by generating concise but …

In this paper, we propose a dynamic graph modeling approach to learn spatial-temporal
representations for video summarization. Most existing video summarization methods extract …

The exponential growth in the production of video contents in different industries causes an
urgent need for effective video summarization (VS) techniques, in order to get an optimal …

Age estimation from a single face image has been an essential task in the field of human-
computer interaction and computer vision, which has a wide range of practical application …