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A General Framework for Deep Supervised Discrete Hashing
Li, Qi; Sun, Zhenan; He, Ran; Tan, Tieniu
Source PublicationInternational Journal of Computer Vision

With the rapid growth of image and video data on the web, hashing has been extensively studied for image or video search in recent years. Benefiting from recent advances in deep learning, deep hashing methods have shown superior performance over the traditional hashing methods. However, there are some limitations of previous deep hashing methods (e.g., the semantic information is not fully exploited). In this paper, we develop a general deep supervised discrete hashing framework based on the assumption that the learned binary codes should be ideal for classification. Both the similarity information and the classification information are used to learn the hash codes within one stream framework. We constrain the outputs of the last layer to be binary codes directly, which is rarely investigated in deep hashing algorithms. Besides, both the pairwise similarity information and the triplet ranking information are exploited in this paper. In addition, two different loss functions are presented: l2 loss and hinge loss, which are carefully designed for the classification term under the one stream framework. Because of the discrete nature of hash codes, an alternating minimization method is used to optimize the objective function. Experimental results have shown that our approach outperforms current state-of-the-art methods on benchmark datasets.

IS Representative Paper
Sub direction classification生物特征识别
planning direction of the national heavy laboratory视觉信息处理
Paper associated data
Document Type期刊论文
Corresponding AuthorSun, Zhenan
AffiliationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Qi,Sun, Zhenan,He, Ran,et al. A General Framework for Deep Supervised Discrete Hashing[J]. International Journal of Computer Vision,2020:2204-2222.
APA Li, Qi,Sun, Zhenan,He, Ran,&Tan, Tieniu.(2020).A General Framework for Deep Supervised Discrete Hashing.International Journal of Computer Vision,2204-2222.
MLA Li, Qi,et al."A General Framework for Deep Supervised Discrete Hashing".International Journal of Computer Vision (2020):2204-2222.
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