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Improvement of deep cross-modal retrieval by generating real-valued representation [PDF]
PeerJ Computer Science, 2021 The cross-modal retrieval (CMR) has attracted much attention in the research community due to flexible and comprehensive retrieval. The core challenge in CMR is the heterogeneity gap, which is generated due to different statistical properties of multi ...
Nikita Bhatt, Amit Ganatra
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Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval [PDF]
EntropyDeep hashing technology, known for its low-cost storage and rapid retrieval, has become a focal point in cross-modal retrieval research as multimodal data continue to grow.
Qiang Zou +3 more
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Learning DALTS for cross-modal retrieval
CAAI Transactions on Intelligence Technology, 2019 Cross-modal retrieval has been recently proposed to find an appropriate subspace, where the similarity across different modalities such as image and text can be directly measured.
Zheng Yu, Wenmin Wang
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Soft Contrastive Cross-Modal Retrieval
Applied SciencesCross-modal retrieval plays a key role in the Natural Language Processing area, which aims to retrieve one modality to another efficiently. Despite the notable achievements of existing cross-modal retrieval methodologies, the complexity of the embedding ...
Jiayu Song +5 more
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InstructSee: Instruction-Aware and Feedback-Driven Multimodal Retrieval with Dynamic Query Generation [PDF]
SensorsIn recent years, cross-modal retrieval has garnered significant attention due to its potential to bridge heterogeneous data modalities, particularly in aligning visual content with natural language.
Guihe Gu +4 more
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Survey of Research Progress on Cross-modal Retrieval [PDF]
Jisuanji kexue, 2021 With the explosive growth of multimedia data on the Internet,single-modal retrieval has been unable to meet the needs of users,and cross-modal retrieval has emerged.Cross-modal retrieval aims to retrieve related data of one modality with data of another ...
FENG Xia, HU Zhi-yi, LIU Cai-hua
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Survey of Research on Deep Learning Image-Text Cross-Modal Retrieval [PDF]
Jisuanji kexue yu tansuo, 2022 As the rapid development of deep neural networks, multi-modal learning techniques are widely concerned. Cross-modal retrieval is an important branch of multimodal learning. Its fundamental purpose is to reveal the relation between different modal samples
LIU Ying, GUO Yingying, FANG Jie, FAN Jiulun, HAO Yu, LIU Jiming
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Cross-Modal Retrieval by Class Information and Listwise Ranking
Jisuanji kexue yu tansuo, 2021 Cross-modal retrieval has attracted significant attention due to the increasing use of multi-modal data. A major challenge for cross-modal retrieval is the modal gap. To cope with the heterogeneity, common subspace learning method is proposed.
LIU Yuping, GE Hong, ZENG Yibin
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SMAN : Stacked Multi-Modal Attention Network for cross-modal image-text retrieval [PDF]
, 2022 This article focuses on tackling the task of the cross-modal image-text retrieval which has been an interdisciplinary topic in both computer vision and natural language processing communities.
Han, Jungong +3 more
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Literature Review of Cross-Modal Retrieval Research
Jisuanji kexue yu tansuo, 2021 With the vigorous development of Internet technology and the popularization of smart devices, while the amount of multimedia data exploding, their forms become increasingly diverse. People's demand for information is no longer satisfied with single-modal
CHEN Ning, DUAN Youxiang, SUN Qifeng
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