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Found 5 papers, 2 papers with code
V-LinkNet: Learning Contextual Inpainting Across Latent Space of Generative Adversarial Network
The RSTL layer easily adapts dual encoders by increasing the unique semantic information through direct communication.
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
We then incorporate the geometry information of a segmentation mask to provide a fine-grained manipulation of facial attributes.
Foreground-guided Facial Inpainting with Fidelity Preservation
It introduces the use of foreground segmentation masks to preserve the fidelity.
R-MNet: A Perceptual Adversarial Network for Image Inpainting
We address the problem by proposing a Wasserstein GAN combined with a new reverse mask operator, namely Reverse Masking Network (R-MNet), a perceptual adversarial network for image inpainting.
Symmetric Skip Connection Wasserstein GAN for High-Resolution Facial Image Inpainting
Additionally, we propose a Wasserstein-Perceptual loss function to preserve colour and maintain realism on a reconstructed image.
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