Image inpainting aims to restore the pixel features of damaged parts in incomplete image
and plays a key role in many computer vision tasks. Image inpainting technology based on …

Abstract Generative Adversarial Networks (GANs) have been extremely successful in
various application domains such as computer vision, medicine, and natural language …

Free-form inpainting is the task of adding new content to an image in the regions specified
by an arbitrary binary mask. Most existing approaches train for a certain distribution of …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

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 …

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

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 …

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 …

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 …

Image inpainting has been widely exploited in the field of computer vision and image
processing. The main purpose of image inpainting is to produce visually plausible structure …