Online Action Detection in Untrimmed, Streaming Videos - Modeling and Evaluation

@article{Shou2018OnlineAD,
  title={Online Action Detection in Untrimmed, Streaming Videos - Modeling and Evaluation},
  author={Zheng Shou and Junting Pan and Jonathan Chan and Kazuyuki Miyazawa and Hassan Mansour and Anthony Vetro and Xavier Gir{\'o} and Shih-Fu Chang},
  journal={CoRR},
  year={2018},
  volume={abs/1802.06822}
}
The goal of Online Action Detection (OAD) is to detect action in a timely manner and to recognize its action category. Early works focused on early action detection, which is effectively formulated as a classification problem instead of online detection in streaming videos, because these works used partially seen short video clip that begins at the start of action. Recently, researchers started to tackle the OAD problem in the challenging setting of untrimmed, streaming videos that contain… CONTINUE READING
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