Multi-modal hashing for efficient multimedia retrieval: A survey
L Zhu, C Zheng, W Guan, J Li, Y Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the explosive growth of multimedia contents, multimedia retrieval is facing
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …
unprecedented challenges on both storage cost and retrieval speed. Hashing technique can …
Work together: Correlation-identity reconstruction hashing for unsupervised cross-modal retrieval
Unsupervised cross-modal hashing has attracted considerable attention to support large-
scale cross-modal retrieval. Although promising progresses have been made so far, existing …
scale cross-modal retrieval. Although promising progresses have been made so far, existing …
Multimodal mutual information maximization: A novel approach for unsupervised deep cross-modal hashing
In this article, we adopt the maximizing mutual information (MI) approach to tackle the
problem of unsupervised learning of binary hash codes for efficient cross-modal retrieval …
problem of unsupervised learning of binary hash codes for efficient cross-modal retrieval …
Multi-manifold deep discriminative cross-modal hashing for medical image retrieval
L Xu, X Zeng, B Zheng, W Li - IEEE Transactions on Image …, 2022 - ieeexplore.ieee.org
Benefitting from the low storage cost and high retrieval efficiency, hash learning has become
a widely used retrieval technology to approximate nearest neighbors. Within it, the cross …
a widely used retrieval technology to approximate nearest neighbors. Within it, the cross …
Multiple deep neural networks with multiple labels for cross-modal hashing retrieval
Y Xie, X Zeng, T Wang, L Xu, D Wang - Engineering Applications of …, 2022 - Elsevier
Most deep hashing methods for cross-modal retrieval use semantic labels to judge simply
whether a pair of data are similar or dissimilar. However, they do not make full use of the …
whether a pair of data are similar or dissimilar. However, they do not make full use of the …
Cross-Modal Retrieval: A Review of Methodologies, Datasets, and Future Perspectives
Z Han, A Azman, MR Mustaffa, FB Khalid - IEEE Access, 2024 - ieeexplore.ieee.org
With the rapid development of science and technology, all types of mixed media contain
large amounts of data. Traditional single multimedia data can no longer satisfy daily …
large amounts of data. Traditional single multimedia data can no longer satisfy daily …
Pseudo Label Association and Prototype-Based Invariant Learning for Semi-Supervised NIR-VIS Face Recognition
Remarkable success of the existing Near-InfraRed and VISible (NIR-VIS) approaches owes
to sufficient labeled training data. However, collecting and tagging data from different …
to sufficient labeled training data. However, collecting and tagging data from different …
[PDF][PDF] Hugs Are Better Than Handshakes: Unsupervised Cross-Modal Transformer Hashing with Multi-granularity Alignment.
The goal of unsupervised cross-modal hashing (UCMH) is to map different modalities into a
semantic-preserving hamming space without requiring label supervision. Existing deep …
semantic-preserving hamming space without requiring label supervision. Existing deep …
Unsupervised deep quadruplet hashing with isometric quantization for image retrieval
Numerous studies have shown deep hashing can facilitate large-scale image retrieval since
it employs neural networks to learn feature representations and binary codes …
it employs neural networks to learn feature representations and binary codes …
One for more: Structured Multi-Modal Hashing for multiple multimedia retrieval tasks
Hashing has been widely studied in support of efficient multimedia retrieval due to its high
computation and storage efficiency. However, existing multimedia hashing models are …
computation and storage efficiency. However, existing multimedia hashing models are …