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Query-Adaptive Summarization.pdf

1705.00581v2.pdf
Preview of Query-Adaptive Summarization
🔗 Source: arxiv.org
📊 Size: 4.77 MB
👤 Author: Arun Balajee Vasudevan[1][2], Michael Gygli[1][2][3], Anna Volokitin[2], Luc Van Gool[2][4]-1.2ex
⬇️ Downloads: 210

Summary

Query-adaptive video summarization is posed as a video frame subset selection problem to optimize for summaries that are diverse, representative, and relevant to a text query. Relevance is quantified by measuring the distance between frames and queries in a common textual-visual semantic embedding space. The model is extended to capture query-independent properties like frame quality. The approach outperforms previous state-of-the-art methods on relevance prediction and introduces a new dataset with diversity and query-specific relevance labels.

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Description

Query-adaptive video summarization is posed as a video frame subset selection problem to optimize for summaries that are diverse, representative, and relevant...

Technical Information

  • File Format: PDF
  • File Size: 4.77 MB
  • Pages: 10
  • Language: EN
  • Author: Arun Balajee Vasudevan[1][2], Michael Gygli[1][2][3], Anna Volokitin[2], Luc Van Gool[2][4]-1.2ex
  • Total Downloads: 210
  • Last Updated: 7 days ago

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