Video summarization via transferrable structured learning
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Video Summarization via Transferrable Structured Learning. Presenter: PENG, Peng 2011-3-29. Outline. Paper present Transfer learning in Social Network. Video Summarization. What is Video Summarization?. Video Summarization. Video Summarization. Assumption in this paper:

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Presentation Transcript

Outline
Outline

  • Paper present

  • Transfer learning in Social Network


Video summarization
Video Summarization

  • What is Video Summarization?



Video summarization2
Video Summarization

  • Assumption in this paper:

    • Each shot is accompanied by certain textual information

    • Textual information and video information are highly correlated (e.g., TV series)









Video summarization10
Video Summarization

  • Problem:

    • How to select some representative shots beforehand?

    • How to know the ground truth?


Transfer learning
Transfer Learning

  • Ds(X, P(X)), Ts(Y, P(Y|X))

  • Dt(X, P(X)), Tt(Y, P(Y|X))

  • In social network, what can be the same and what can be different?




Transfer learning in social networks
Transfer Learning in Social Networks

  • Large amounts of unlabeled data

  • How to avoid negative transfer?


Topics in social networks
Topics in Social Networks

  • Community Detection and Graph-based Clustering

  • Information Influence, Diffusion and Outbreak Detection

  • Link Prediction and Collaborative Filtering

  • Social Tagging and Learning

  • Collective intelligence and Crowd-sourcing


Transfer learning1
Transfer Learning

  • What is the sufficient and necessary condition for positive transfer?

  • How to keep consistency between the source data and the target data?

  • How to guarantee the correctness of the transferred data in the target tasks?

  • What is the way to measure the relatedness between two different tasks?


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