Summary of Ubiss: a Unified Framework For Bimodal Semantic Summarization Of Videos, by Yuting Mei et al.
UBiSS: A Unified Framework for Bimodal Semantic Summarization of Videos
by Yuting Mei, Linli Yao, Qin Jin
First submitted to arxiv on: 24 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Multimedia (cs.MM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A unified framework for bimodal video summarization is proposed, which simultaneously generates a textual and visual summary of videos. The framework, called UBiSS, models saliency information in the video and uses a list-wise ranking-based objective to improve its ability to capture highlights. The performance of UBiSS is evaluated using a novel metric, NDCG_{MS}, and is shown to outperform multi-stage summarization pipelines. The framework’s effectiveness is demonstrated on a large-scale dataset, BIDS, which includes video data, textual summaries, and visual summaries. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Video summarization techniques are becoming increasingly important as the amount of video data continues to grow. However, traditional unimodal summarization methods can lose the rich semantics of videos. To address this issue, researchers have proposed a new task called Bimodal Semantic Summarization of Videos (BiSSV). This involves generating both textual and visual summaries of videos that capture their most important and meaningful content. A team of scientists has developed a framework for achieving BiSSV, which they call UBiSS. UBiSS uses a unique approach to model saliency information in the video and generate summaries simultaneously. The framework’s effectiveness is evaluated using a novel metric, NDCG_{MS}. Overall, this research has the potential to greatly improve our ability to summarize videos effectively. |
Keywords
» Artificial intelligence » Semantics » Summarization
