Beyond Context: Exploring Semantic Similarity for Tiny Face Detection

@article{Xi2018BeyondCE,
  title={Beyond Context: Exploring Semantic Similarity for Tiny Face Detection},
  author={Yue Xi and Jiangbin Zheng and Xiangjian He and Wenjing Jia and Hanhui Li},
  journal={2018 25th IEEE International Conference on Image Processing (ICIP)},
  year={2018},
  pages={1907-1911}
}
  • Yue XiJiangbin Zheng Hanhui Li
  • Published 5 March 2018
  • Computer Science
  • 2018 25th IEEE International Conference on Image Processing (ICIP)
Tiny face detection aims to find faces with high degrees of variability in scale, resolution and occlusion in cluttered scenes. Due to the very little information available on tiny faces, it is not sufficient to detect them merely based on the information presented inside the tiny bounding boxes or their context. In this paper, we propose to exploit the semantic similarity among all predicted targets in each image to boost current face detectors. To this end, we present a novel framework to… 

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