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Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22853
Abstract: Cross‐modal retrieval has attracted great attention due to the increasing demand for tremendous amounts of multimodal data in recent years. These retrievals could either be text‐to‐image or image‐to‐text. To address the problem of inappropriate information…
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Keywords:
deep regularized;
cross modal;
modal retrieval;
regularized hashing ... See more keywords
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Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7343-8
Abstract: Cross-modal retrieval aims to search the semantically similar instances from the other modalities given a query from one modality. However, the differences of the distributions and representations between different modalities make that the similarity of…
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Keywords:
different modalities;
semantic similarity;
similarity;
cross modal ... See more keywords
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Published in 2025 at "Data Science and Engineering"
DOI: 10.1007/s41019-025-00282-1
Abstract: Hashing-based unsupervised cross-modal retrieval has gained significant attention in the big data management community due to its low storage overhead and rapid retrieval speed. However, current methods often lack effective alignment strategies to reduce the…
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Keywords:
cross modal;
modal;
graph;
modal retrieval ... See more keywords
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Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.01.114
Abstract: Abstract Cross-modal retrieval is an important but challenging research task in the multimedia community. Most existing works of this task are supervised, which typically train models on a large number of aligned image-text/video-text pairs, making…
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Keywords:
retrieval;
alignment;
cross modal;
cross ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2966220
Abstract: Most of the existing cross-modal retrieval methods make use of labeled data to learn projection matrices for different modal data. These methods usually learn the original semantic space to bridge the heterogeneous gap, ignoring the…
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Keywords:
semantic consistency;
cross modal;
modal retrieval;
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Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3526939
Abstract: As a pivotal link between visual and linguistic relationships, image-text cross-modal retrieval has received widespread attention. However, existing studies primarily focus on intricate machine learning models to enhance retrieval accuracy and overlook the critical aspect…
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Keywords:
cross modal;
iot;
retrieval;
modal retrieval ... See more keywords
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1
Published in 2022 at "IEEE Intelligent Systems"
DOI: 10.1109/mis.2022.3169884
Abstract: As a general characteristic observed in the real-world datasets, multimodal data are usually partially associated, which comprise the commonly shared information across modalities (i.e., modality-shared information) and the specific information only exists in a single…
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Keywords:
information;
modality;
cross modal;
modal retrieval ... See more keywords
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Published in 2022 at "IEEE MultiMedia"
DOI: 10.1109/mmul.2022.3144138
Abstract: The main challenge of cross-modal retrieval is how to efficiently realize cross-modal semantic alignment and reduce the heterogeneity gap. However, existing approaches either ignore the multigrained semantic knowledge learning from different modalities, or fail to…
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Keywords:
deep multigraph;
cross modal;
modal retrieval;
cross ... See more keywords
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Published in 2025 at "IEEE Transactions on Consumer Electronics"
DOI: 10.1109/tce.2025.3603210
Abstract: Cross-modal retrieval presents significant challenges for consumer technology applications, demanding innovative approaches to bridge semantic gaps between different data modalities while ensuring efficient information access. This paper introduces a novel Self-Reinforcement and Quadruplet Alignment Hashing…
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Keywords:
cross modal;
alignment;
modal;
modal retrieval ... See more keywords
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Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3182549
Abstract: Cross-modal retrieval aims at retrieving highly semantic relevant information among multi-modalities. Existing cross-modal retrieval methods mainly explore the semantic consistency between image and text while rarely consider the rankings of positive instances in the retrieval…
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Keywords:
modal retrieval;
retrieval;
ranking learning;
cross modal ... See more keywords
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Published in 2023 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3203247
Abstract: Cross-modal retrieval tasks, which are more natural and challenging than traditional retrieval tasks, have attracted increasing interest from researchers in recent years. Although different modalities with the same semantics have some potential relevance, the feature…
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Keywords:
cross;
common space;
cross modal;
modal retrieval ... See more keywords