Learning Deep Binary Descriptor with Multi-quantization

@article{Duan2017LearningDB,
  title={Learning Deep Binary Descriptor with Multi-quantization},
  author={Yueqi Duan and Jiwen Lu and Ziwei Wang and Jianjiang Feng and Jie Zhou},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={4857-4866}
}
In this paper, we propose an unsupervised feature learning method called deep binary descriptor with multi-quantization (DBD-MQ) for visual matching. Existing learning-based binary descriptors such as compact binary face descriptor (CBFD) and DeepBit utilize the rigid sign function for binarization despite of data distributions, thereby suffering from severe quantization loss. In order to address the limitation, our DBD-MQ considers the binarization as a multi-quantization task. Specifically… CONTINUE READING

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