Exposure correction tasks are dedicated to recovering the brightness and structural
information of overexposed or underexposed images. The recovery difficulty of areas with …

We study the problem of contextual outpainting, which aims to hallucinate the missing
background contents based on the remaining foreground contents. Existing image …

The purpose of image inpainting is to recover scratches and damaged areas using context
information from remaining parts. In recent years, with the development of convolutional …

Recent advances in image inpainting have shown impressive results for generating
plausible visual details on rather simple backgrounds. However, for complex scenes, it is still …

Generic image inpainting aims to complete a corrupted image by borrowing surrounding
information, which barely generates novel content. By contrast, multi-modal inpainting …

Image inpainting is an essential task for multiple practical applications like object removal
and image editing. Deep GAN-based models greatly improve the inpainting performance in …

Completing a corrupted image with correct structures and reasonable textures for a mixed
scene remains an elusive challenge. Since the missing hole in a mixed scene of a corrupted …

Image inpainting has made great progress with the emergence of deep learning. However,
there are also problems of structural loss and blurry textures, which lead to the generated …

Recent attention-based image inpainting methods have made inspiring progress by
propagating distant contextual information into holes. However, they tend to generate blurry …

In this paper, we address the task of semantics-guided image outpainting, which is to
complete an image by generating semantically practical content. Different from most existing …