Deep Cross-Modal Hashing
Nanjing University of Science and Technology
Abstract
Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been widely used for similarity search in multimedia retrieval applications. However, most existing CMH methods are based on hand-crafted features which might not be optimally compatible with the hash-code learning procedure. As a result, existing CMH methods with hand-crafted features may not achieve satisfactory performance. In this paper, we propose a novel CMH method, called deep cross-modal hashing (DCMH), by integrating feature learning and hash-code learning intothe same framework. DCMH is an end-to-end learning framework with deep neural networks, one for each modality, to perform feature learning from scratch. Experiments…
Citation impact
- FWCI
- 27.91
- Percentile
- 100%
- References
- 66
Authors
2Topics & keywords
- Computer science
- Hash function
- Deep learning
- Modal
- Feature (linguistics)
- Modality (human–computer interaction)
- Code (set theory)
- Artificial intelligence