Images can be described as visual representations or likeness of something (person or
object) which can be reproduced or captured, eg a hand drawing, photographic material …

Image inpainting refers to the process of restoring missing or damaged areas in an image.
This field of research has been very active over recent years, boosted by numerous …

Given an incomplete image without additional constraint, image inpainting natively allows
for multiple solutions as long as they appear plausible. Recently, multiple-solution inpainting …

Recently data-driven image inpainting methods have made inspiring progress, impacting
fundamental image editing tasks such as object removal and damaged image repairing …

We present a generative image inpainting system to complete images with free-form mask
and guidance. The system is based on gated convolutions learned from millions of images …

The latest deep learning-based approaches have shown promising results for the
challenging task of inpainting missing regions of an image. However, the existing methods …

We present a novel approach for image completion that results in images that are both
locally and globally consistent. With a fully-convolutional neural network, we can complete …

Deep convolutional networks (CNNs) have exhibited their potential in image inpainting for
producing plausible results. However, in most existing methods, eg, context encoder, the …

Recent advances in deep learning have shown exciting promise in filling large holes in
natural images with semantically plausible and context aware details, impacting …

We present a new flow-based video completion algorithm. Previous flow completion
methods are often unable to retain the sharpness of motion boundaries. Our method first …