Alleviating the inconsistency of multimodal data in cross-modal retrieval

• Main Authors: Li, Tieying, Yang, Xiaochun, Ke, Yiping, Wang, Bin, Liu, Yinan, Xu, Jiaxing
• Other Authors: College of Computing and Data Science
• Format: Conference or Workshop Item
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Disentangled hash learning; Cross-modal retrieval; Cross-modal hashing; Label refinement; Cross-modal common semantic alignment
• Online Access: https://hdl.handle.net/10356/180605
• Institution: Nanyang Technological University

With the explosive growth of multimodal Internet data, cross-modal hashing retrieval has become crucial for semantically searching instances across different modalities. However, existing cross-modal retrieval methods rely on assumptions of perfect consistency between modalities and between modaliti...