CMOS-GAN: Semi-supervised Generative Adversarial Model for Cross-Modality Face Image Synthesis

Cross-modality face image synthesis such as sketch-to-photo, NIR-to-RGB, and RGB-to-depth has wide applications in face recognition, face animation, and digital entertainment. Conventional cross-modality synthesis methods usually require paired training data, i.e., each subject has images of both mo...

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Vydané v:	IEEE transactions on image processing Ročník 32; s. 1
Hlavní autori:	Yu, Shikang, Han, Hu, Shan, Shiguang, Chen, Xilin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Animation CMOS Coders cross-modality face recognition Cross-modality synthesis Datasets Encoders-Decoders Face recognition generative adversarial networks Image acquisition semi-supervised synthesis Source code Synthesis
ISSN:	1057-7149, 1941-0042, 1941-0042
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