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Efficient Hash Code Expansion by Recycling Old Bits by Dayan Wu; Qinghang Su; Bo Li; Weiping Wang is a scholarly article available to read on EtoBox.

What is Efficient Hash Code Expansion by Recycling Old Bits about?

Deep hashing methods have been intensively studied and successfully applied in large-scale multimedia retrieval. In real-world scenarios, code length can not be set once for all if retrieval accuracy is not satisfying. However, when code length increases, conventional deep hashing methods have to retrain their models and regenerate the whole database codes, which is impractical for large-scale retrieval system. In this paper, we propose an interesting deep hashing method from a brand new perspective, called Code Expansion oriented Deep Hashing (CEDH). Different from conventional deep hashing methods, our CEDH focuses on the fast expansion of existing hash codes. Instead of regenerating all bits from raw images, the new bits in CEDH can be incrementally learned by recycling the old ones. Specifically, we elaborately design an end-to-end asymmetric framework to simultaneously optimize a CNN model for query images and a code projection matrix for database images. With the learned code projection matrix, hash codes can achieve fast expansion through simple matrix multiplication. Subsequently, a novel code expansion hashing loss is proposed to preserve the similarities between query cod

Author

Dayan Wu; Qinghang Su; Bo Li; Weiping Wang

Publisher

ACM

Published

2022

Language

EN