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Facial attribute-controlled sketch-to-image translation with generative adversarial networks
2020
EURASIP Journal on Image and Video Processing
Due to the rapid development of the generative adversarial networks (GANs) and convolution neural networks (CNN), increasing attention is being paid to face synthesis. In this paper, we address the new and challenging task of facial sketch-to-image synthesis with multiple controllable attributes. To achieve this goal, first, we propose a new attribute classification loss to ensure that the synthesized face image with the facial attributes, which the users desire to have. Second, we employ the
doi:10.1186/s13640-020-0489-5
fatcat:h3nnm7qg2ffirdhkqphfuahvmi