Image inpainting is an important research direction in the study of computer vision, and is
widely used in image editing and photo inpainting etc. Traditional image inpainting …

Although image inpainting, or the art of repairing the old and deteriorated images, has been
around for many years, it has recently gained even more popularity, because of the recent …

Recent studies have shown the importance of modeling long-range interactions in the
inpainting problem. To achieve this goal, existing approaches exploit either standalone …

Most image inpainting algorithms have problems such as fuzzy images, texture distortion
and semantic inaccuracy, and the image inpainting effect is limited when processing photos …

Modern image inpainting systems, despite the significant progress, often struggle with large
missing areas, complex geometric structures, and high-resolution images. We find that one …

Abstract Neural Radiance Fields (NeRFs) have emerged as a popular approach for novel
view synthesis. While NeRFs are quickly being adapted for a wider set of applications …

Deep generative approaches have recently made considerable progress in image
inpainting by introducing structure priors. Due to the lack of proper interaction with image …

We propose PD-GAN, a probabilistic diverse GAN forimage inpainting. Given an input image
with arbitrary holeregions, PD-GAN produces multiple inpainting results withdiverse and …

In view of the faultiness that the existing image inpainting methods fail to make full use of the
complete region to predict the missing region features when the object features are seriously …

Existing inpainting methods have achieved promising performance for recovering regular or
small image defects. However, filling in large continuous holes remains difficult due to the …