… existing self-attention-based summarization methods, we propose a novel supervised
approach, called PGL-SUM, which integrates an absolute positional encoding component into a …

… video summarization task by formulating it as a sequential decision-making process, in which
the input is a sequence of video … an attention-based hierarchical LSTM module for video …

… model is based on the supervised attention-based encoder-decoder network of [13]. Since
… is entirely replaced by an attention auto-encoder (AAE) network. The architecture of the new …

… To solve this problem, [25] discards the LSTM and employs a self-attention based network,
which … of videos based on the encoder-decoder structure and achieve better performance. …

… approach for supervised video summarization. Different from … long short-term memory
networks, our method exploits the … networks (Cycle-SUM) [8], attention-based encoder-decoder …

… works on supervised video summarization, unsupervised video summarization and …
attention-based network to predict the final importance score sequence. Our attention-based network …

… Recently, attention-based video summarization methods have become increasingly popular
and have achieved good results. Therefore, in the following subsections, we will review …

… of producing a comprehensive video summary following an unsupervised … video
summarization as a keysegment selection problem. We adopt a GAN-based video summarization …

… (2020) used attentionbased LSTM networks for the decoder … , which is important to encode
the semantic relations within key frames… attention networks (GCANs) for video summarization. …

… The attention networks can decrease computational … of attentionbased supervised video
summarization approaches are proposed. Fajtl et al. [6] designed a video summarization model …