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Found 4 papers, 3 papers with code
Video Summarization Using Deep Neural Networks: A Survey
Video summarization technologies aim to create a concise and complete synopsis by selecting the most informative parts of the video content.
AC-SUM-GAN: Connecting Actor-Critic and Generative Adversarial Networks for Unsupervised Video Summarization
This paper presents a new method for unsupervised video summarization.
Ranked #3 on
Unsupervised Video Summarization
on TvSum
Generative Adversarial Network
Unsupervised Video Summarization
Unsupervised Video Summarization via Attention-Driven Adversarial Learning
Experimental evaluation on two datasets (SumMe and TVSum) documents the contribution of the attention auto-encoder to faster and more stable training of the model, resulting in a significant performance improvement with respect to the original model and demonstrating the competitiveness of the proposed SUM-GAN-AAE against the state of the art.
Ranked #6 on
Unsupervised Video Summarization
on SumMe
A Stepwise, Label-based Approach for Improving the Adversarial Training in Unsupervised Video Summarization
In this paper we present our work on improving the efficiency of adversarial training for unsupervised video summarization.
Ranked #5 on
Unsupervised Video Summarization
on TvSum
