Cited by 45Video Surveillance and Tracking MethodsFace recognition and analysisAdvanced Image and Video Retrieval Techniques

Modality-transfer generative adversarial network and dual-level unified latent representation for visible thermal Person re-identification

Fan, Xing, Jiang, Wei, Luo, Hao, Mao, Weijie·2022·The Visual Computer

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Crossref · 10.1007/s00371-020-02015-z

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55 of 55 references verified0 citation errors · 0 not checkable

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  • The generative adversarial learning paradigm has recently been widely adopted in multimodal arenas such as image captioning and image retrieval.

    “In addition to its use in unimodal applications, the generative adversarial learning paradigm has recently been widely adopted in multimodal arenas, where two or more modalities are involved, such as image captioning [227] and image retrieval [228].”

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Authors
Fan, X., Jiang, W., Luo, H., & Mao, W.
Affiliations
State Key Laboratory of Industrial Control Technology (CN)
Corresponding author
Jiang, Wei
Venue
The Visual Computer
Published
2020-11-24
Volume
38
Issue
1
Pages
279-294
ISSN
  • 0178-2789 (ISSN-L)
  • 1432-2315
OpenAlex
W3106715297
Cited by
45
References
55
Citations by year
2026: 4 · 2025: 3 · 2024: 16 · 2023: 12 · 2022: 8 · 2021: 2
FWCI
2.14
Type
journal article
Language
en
Open access
closed
Locations
The Visual Computer (publishedVersion)
Funders
  • National Natural Science Foundation of China (No. 61633019)
  • Public Projects of Zhejiang Province (No. LGF18F030002)
  • Science Foundation of Chinese Aerospace Industry (JCKY2018204B053)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
Keywords
modality transfer, generative adversarial networks, near-infrared imagery

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