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Generation of fonts
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Font style transfer and content consistency.
Task analysis, Generative adversarial networks, Topology,
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Font generation, Style transfer, Transformers
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PAMI(45), No. 7, July 2023, pp. 9122-9134.
IEEE DOI
2306
Training, Generators, Text recognition, Standards, Image recognition,
Generative adversarial networks, Task analysis,
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Task analysis, Libraries, Feature extraction, Data models,
Visualization, Training, Skeleton, Few-shot font generation,
computer vision
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CVPR23(22438-22447)
IEEE DOI
2309
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CVPR23(1858-1867)
IEEE DOI
2309
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Xiong, B.[Bojun],
Lian, Z.H.[Zhou-Hui],
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CVPR23(1848-1857)
IEEE DOI
2309
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Zhang, Z.F.[Zhi-Fei],
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Fisher, M.[Matthew],
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CVPR23(14193-14202)
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2309
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Zhu, Y.S.[Yue-Sheng],
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CVPR23(18320-18328)
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2309
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Font Generation with Missing Impression Labels,
ICPR22(1400-1406)
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2212
Training, Image coding, Codes, Generative adversarial networks,
Data models
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Aizawa, K.[Kiyoharu],
SVG Vector Font Generation for Chinese Characters with Transformer,
ICIP22(646-650)
IEEE DOI
2211
Shape, Network architecture, Transformers,
Rendering (computer graphics), Vector font generation, Transformer
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Kong, Y.X.[Yu-Xin],
Luo, C.J.[Can-Jie],
Ma, W.H.[Wei-Hong],
Zhu, Q.Y.[Qi-Yuan],
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Yuan, N.[Nicholas],
Jin, L.W.[Lian-Wen],
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CVPR22(13472-13481)
IEEE DOI
2210
Couplings, Generators, Adversarial machine learning,
Pattern recognition, Complexity theory, Low-level vision
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Tang, L.C.[Li-Cheng],
Cai, Y.Y.[Yi-Yang],
Liu, J.M.[Jia-Ming],
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Ding, E.[Errui],
Wang, J.D.[Jing-Dong],
Few-Shot Font Generation by Learning Fine-Grained Local Styles,
CVPR22(7885-7894)
IEEE DOI
2210
Costs, Aggregates, Computational modeling, Pipelines, Libraries,
Data models, Image and video synthesis and generation,
Transfer/low-shot/long-tail learning
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Liu, W.[Wei],
Liu, F.[Fangyue],
Ding, F.[Fei],
He, Q.[Qian],
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CVPR22(7895-7904)
IEEE DOI
2210
Representation learning, Image resolution, Correlation,
Machine vision, Transformers, Libraries,
Vision applications and systems
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Xie, Y.C.[Yang-Chen],
Chen, X.Y.[Xin-Yuan],
Sun, L.[Li],
Lu, Y.[Yue],
DG-Font: Deformable Generative Networks for Unsupervised Font
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CVPR21(5126-5136)
IEEE DOI
2111
Deformable models, Convolution, Image color analysis, Computational modeling,
Writing
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Wen, C.[Chuan],
Pan, Y.J.[Yu-Jie],
Chang, J.[Jie],
Zhang, Y.[Ya],
Chen, S.H.[Si-Heng],
Wang, Y.F.[Yan-Feng],
Han, M.[Mei],
Tian, Q.[Qi],
Handwritten Chinese Font Generation with Collaborative Stroke
Refinement,
WACV21(3881-3890)
IEEE DOI
2106
Training, Adaptation models,
Computational modeling, Collaboration, Character generation
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Li, C.H.[Chen-Hao],
Taniguchi, Y.[Yuta],
Lu, M.[Min],
Konomi, S.[Shin'ichi],
Few-shot Font Style Transfer between Different Languages,
WACV21(433-442)
IEEE DOI
2106
Training, Computational modeling,
Computer architecture, Libraries, Task analysis
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Park, S.[Song],
Chun, S.[Sanghyuk],
Cha, J.[Junbum],
Lee, B.[Bado],
Shim, H.J.[Hyun-Jung],
Multiple Heads are Better than One:
Few-shot Font Generation with Multiple Localized Experts,
ICCV21(13880-13889)
IEEE DOI
2203
Training, Head, Codes, Feature extraction, Image and video synthesis,
Neural generative models, Vision applications and systems
BibRef
Aoki, H.[Haruka],
Tsubota, K.[Koki],
Ikuta, H.[Hikaru],
Aizawa, K.[Kiyoharu],
Few-Shot Font Generation with Deep Metric Learning,
ICPR21(8539-8546)
IEEE DOI
2105
Measurement, Visualization, Image color analysis,
Feature extraction, Skeleton, Pattern recognition, Task analysis
BibRef
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Language Recognition, Multi-Language Documents .