Explore instance similarity: An instance correlation based hashing method for multi-label cross-model retrieval

Highlights：

• The main contributions can be summarized as follows:

• We define instance similarity and then utilize it to guide the cross-modal hashing learning. By using the instance similarity, the network is able to learn the minor difference between specific instances.

• We propose an end-to-end cross-modal hashing framework to bridge intra-modal and cross-modal relationship, which integrates semantic feature learning and hash code learning into the same deep learning architecture.

• Extensive experiments in different datasets demonstrate the outstanding performance of our methods compared to other state-of-the-art cross-modal hashing methods.