• DOI:10.1016/j.patcog.2020.107275
Corpus ID: 53720496

Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection

@article{Zhou2020GlobalAL,
  title={Global and Local Sensitivity Guided Key Salient Object Re-augmentation for Video Saliency Detection},
  author={Ziqi Zhou and Z. Wang and H. Lu and S. Wang and M. Sun},
  journal={Pattern Recognit.},
  year={2020},
  volume={103},
  pages={107275}
}

Ziqi Zhou, Z. Wang, +2 authors M. Sun

Published 2020

Computer Science

Pattern Recognit.

The existing still-static deep learning based saliency researches do not consider the weighting and highlighting of extracted features from different layers, all features contribute equally to the final saliency decision-making. Such methods always evenly detect all "potentially significant regions" and unable to highlight the key salient object, resulting in detection failure of dynamic scenes. In this paper, based on the fact that salient areas in videos are relatively small and concentrated… CONTINUE READING

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