A GAN for image inpainting that feeds pretrained attribute and segmentation predictions into the generator and uses three discriminators to enforce semantic consistency achieves small gains in PSNR/SSIM over existing methods.
An aug- mented lagrangian approach to the constrained optimization formulation of imaging inverse problems,
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Boosted GAN with Semantically Interpretable Information for Image Inpainting
A GAN for image inpainting that feeds pretrained attribute and segmentation predictions into the generator and uses three discriminators to enforce semantic consistency achieves small gains in PSNR/SSIM over existing methods.