Cross-Modality Binary Code Learning via Fusion Similarity Hashing

@article{Liu2017CrossModalityBC,
  title={Cross-Modality Binary Code Learning via Fusion Similarity Hashing},
  author={Hong W. Liu and Rongrong Ji and Yongjian Wu and Feiyue Huang and Baochang Zhang},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={6345-6353}
}
Binary code learning has been emerging topic in large-scale cross-modality retrieval recently. It aims to map features from multiple modalities into a common Hamming space, where the cross-modality similarity can be approximated efficiently via Hamming distance. To this end, most existing works learn binary codes directly from data instances in multiple modalities, which preserve both intra-and inter-modal similarities respectively. Few methods consider to preserve the fusion similarity among… CONTINUE READING

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