8 citations · 9 across the 3 of their papers we have counts for
5 papers
V-LinkNet: Learning Contextual Inpainting Across Latent Space of Generative Adversarial Network
Jireh Jam, Connah Kendrick, Vincent Drouard +2
Image inpainting is a key technique in image processing task to predict the missing regions and generate realistic images. Given the advancement of existing generative inpainting m…
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
Ricard Durall, Jireh Jam, Dominik Strassel +2
Facial image manipulation is a generation task where the output face is shifted towards an intended target direction in terms of facial attribute and styles. Recent works have achi…
Foreground-guided Facial Inpainting with Fidelity Preservation
Jireh Jam, Connah Kendrick, Vincent Drouard +2
Facial image inpainting, with high-fidelity preservation for image realism, is a very challenging task. This is due to the subtle texture in key facial features (component) that ar…
R-MNet: A Perceptual Adversarial Network for Image Inpainting
Jireh Jam, Connah Kendrick, Vincent Drouard +3
Facial image inpainting is a problem that is widely studied, and in recent years the introduction of Generative Adversarial Networks, has led to improvements in the field. Unfortun…
Symmetric Skip Connection Wasserstein GAN for High-Resolution Facial Image Inpainting
Jireh Jam, Connah Kendrick, Vincent Drouard +3
The state-of-the-art facial image inpainting methods achieved promising results but face realism preservation remains a challenge. This is due to limitations such as; failures in p…