Corpus ID: 18324116

A Pursuit of Temporal Accuracy in General Activity Detection

@article{Xiong2017APO,
  title={A Pursuit of Temporal Accuracy in General Activity Detection},
  author={Yuanjun Xiong and Y. Zhao and L. Wang and D. Lin and X. Tang},
  journal={ArXiv},
  year={2017},
  volume={abs/1703.02716}
}
  • Yuanjun Xiong, Y. Zhao, +2 authors X. Tang
  • Published 2017
  • Computer Science
  • ArXiv
  • Detecting activities in untrimmed videos is an important but challenging task. [...] Key Method The other contribution is a cascaded classification pipeline that explicitly distinguishes between relevance and completeness of a candidate instance. On two challenging temporal activity detection datasets, THUMOS14 and ActivityNet, the proposed framework significantly outperforms the existing state-of-the-art methods, demonstrating superior accuracy and strong adaptivity in handling activities with various temporal…Expand Abstract

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