Corpus ID: 221090058

A Unified Framework for Shot Type Classification Based on Subject Centric Lens

  title={A Unified Framework for Shot Type Classification Based on Subject Centric Lens},
  author={Anyi Rao and Jiaze Wang and Linning Xu and Xuekun Jiang and Q. Huang and B. Zhou and D. Lin},
  • Anyi Rao, Jiaze Wang, +4 authors D. Lin
  • Published 2020
  • Computer Science, Engineering
  • Shots are key narrative elements of various videos, e.g. movies, TV series, and user-generated videos that are thriving over the Internet. The types of shots greatly influence how the underlying ideas, emotions, and messages are expressed. The technique to analyze shot types is important to the understanding of videos, which has seen increasing demand in real-world applications in this era. Classifying shot type is challenging due to the additional information required beyond the video content… CONTINUE READING

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    Publications referenced by this paper.
    Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
    • 1,821
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    • PDF
    Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
    • 1,479
    • PDF
    A unified framework for semantic shot classification in sports video
    • 98
    • PDF
    Deep Residual Learning for Image Recognition
    • 50,533
    • Highly Influential
    • PDF
    Temporal Action Detection with Structured Segment Networks
    • 206
    • PDF
    ImageNet Large Scale Visual Recognition Challenge
    • 16,498
    • PDF
    ActivityNet: A large-scale video benchmark for human activity understanding
    • 779
    • PDF
    R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
    • 292
    • PDF
    Shot classification in sports video
    • 16
    Using context saliency for movie shot classification
    • 17
    • PDF