Temporal Tessellation: A Unified Approach for Video Analysis

@article{Kaufman2016TemporalTA,
  title={Temporal Tessellation: A Unified Approach for Video Analysis},
  author={Dotan Kaufman and Gil Levi and Tal Hassner and Lior Wolf},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2016},
  pages={94-104}
}
  • Dotan Kaufman, Gil Levi, +1 author Lior Wolf
  • Published in
    IEEE International Conference…
    2016
  • Computer Science
  • We present a general approach to video understanding, inspired by semantic transfer techniques that have been successfully used for 2D image analysis. Our method considers a video to be a 1D sequence of clips, each one associated with its own semantics. The nature of these semantics – natural language captions or other labels – depends on the task at hand. A test video is processed by forming correspondences between its clips and the clips of reference videos with known semantics, following… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 79 REFERENCES

    Movie Description

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Visually Indicated Sounds

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    TVSum: Summarizing web videos using titles

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    THUMOS challenge: Action recognition with a large number of classes

    • Y.-G. Jiang, J. Liu, +4 authors R. Sukthankar
    • http: //crcv.ucf.edu/THUMOS14/
    • 2014
    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Summary Transfer: Exemplar-Based Subset Selection for Video Summarization

    VIEW 2 EXCERPTS

    Temporal Action Detection Using a Statistical Language Model