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 …

Image Inpainting is an age-old image processing problem, with people from different eras
attempting to solve it using various methods. Traditional image inpainting algorithms have …

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 …

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 …

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 …

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 …

Image inpainting has made significant advances in recent years. However, it is still
challenging to recover corrupted images with both vivid textures and reasonable structures …

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

Recent advances in image editing techniques have posed serious challenges to the
trustworthiness of multimedia data, which drives the research of image tampering detection …

Image inpainting is generally done using either a domain-specific (preconditioned) model or
a generic model that is postconditioned at inference time. Preconditioned models are fast at …