Contrastive Losses Are Natural Criteria for Unsupervised Video Summarization-Reference-Cited by-同舟云学术

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Contrastive Losses Are Natural Criteria for Unsupervised Video Summarization

Published:2023-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
language:
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Author:

Pang Zongshang¹,Nakashima Yuta¹,Otani Mayu²,Nagahara Hajime¹

Affiliation:

1. Osaka University

2. CyberAgent, Inc.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030858.pdf?arnumber=10030858

Reference63 articles.

1. Attentive and Adversarial Learning for Video Summarization

2. Retrospective Encoders for Video Summarization

3. Extractive Video Summarizer with Memory Augmented Neural Networks

4. Video Summarization with Long Short-Term Memory

5. Video summarization by learning submodular mixtures of objectives

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. UBiSS: A Unified Framework for Bimodal Semantic Summarization of Videos;Proceedings of the 2024 International Conference on Multimedia Retrieval;2024-05-30

2. Unsupervised Video Summarization Based on the Diffusion Model of Feature Fusion;IEEE Transactions on Computational Social Systems;2024

3. A Systematic Study on Video Summarization: Approaches, Challenges, and Future Directions;Proceedings of the 2nd Workshop on User-centric Narrative Summarization of Long Videos;2023-10-29

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