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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Video Summarization via Transferrable Structured Learning

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Video summarization via transferrable structured learning

Video Summarization via Transferrable Structured Learning

Presenter: PENG, Peng

2011-3-29


Outline

Outline

  • Paper present

  • Transfer learning in Social Network


Video summarization

Video Summarization

  • What is Video Summarization?


Video summarization1

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 summarization3

Video Summarization


Video summarization4

Video Summarization


Video summarization5

Video Summarization


Video summarization6

Video Summarization


Video summarization7

Video Summarization


Video summarization8

Video Summarization


Video summarization9

Video Summarization


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?


Video summarization via transferrable structured learning

  • Q&A


Thank you

Thank You!


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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