Graph-collaborated auto-encoder hashing for multiview binary clustering
H Wang, M Yao, G Jiang, Z Mi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unsupervised hashing methods have attracted widespread attention with the explosive
growth of large-scale data, which can greatly reduce storage and computation by learning …
growth of large-scale data, which can greatly reduce storage and computation by learning …
Multi-modal hashing for efficient multimedia retrieval: A survey
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 …
A survey on deep hashing methods
Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …
distances from them to the queries, which is a basic task in a range of fields, including …
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 …
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 …
Multiple instance relation graph reasoning for cross-modal hash retrieval
The similarity calculation is too simple in most cross-modal hash retrieval methods, which do
not consider the impact of the relations between instances. To solve this problem, this paper …
not consider the impact of the relations between instances. To solve this problem, this paper …
Semantically meaningful class prototype learning for one-shot image segmentation
One-shot semantic image segmentation aims to segment the object regions for the novel
class with only one annotated image. Recent works adopt the episodic training strategy to …
class with only one annotated image. Recent works adopt the episodic training strategy to …
Similarity Graph-correlation Reconstruction Network for unsupervised cross-modal hashing
Existing cross-modal hash retrieval methods can simultaneously enhance retrieval speed
and reduce storage space. However, these methods face a major challenge in determining …
and reduce storage space. However, these methods face a major challenge in determining …
Adaptive structural similarity preserving for unsupervised cross modal hashing
Cross-modal hashing is an important approach for multimodal data management and
application. Existing unsupervised cross-modal hashing algorithms mainly rely on data …
application. Existing unsupervised cross-modal hashing algorithms mainly rely on data …
Data-aware proxy hashing for cross-modal retrieval
Recently, numerous proxy hash code based methods, which sufficiently exploit the label
information of data to supervise the training of hashing models, have been proposed …
information of data to supervise the training of hashing models, have been proposed …