Image inpainting aims to generate realistic content for missing regions of an image. Existing
methods often struggle to produce visually coherent content for missing regions of an image …

Image inpainting is currently a hot topic within the field of computer vision. It offers a viable
solution for various applications, including photographic restoration, video editing, and …

Transformer models have achieved state-of-the-art results in many applications like NLP
classification etc. But their exploration in gesture recognition task is still limited. So we …

Abnormalities in the gastrointestinal tract significantly influence the patient's health and
require a timely diagnosis for effective treatment. With such consideration, an effective …

Abstract Document Image Inpainting (DII) has been applied to degraded documents,
including financial and historical documents, to enhance the legibility of images for:(1) …

Video inpainting aims to fill in corrupted regions of the video with plausible contents. Existing
methods generally assume that the locations of corrupted regions are known, focusing …

Blind image inpainting, aiming to recover contaminated images in the case of unknown
masks, is a challenging task. Motivated by the perspective of human vision and knowledge …

Image inpainting has made remarkable progress through deep learning methods.
Nevertheless, owing to the flaws of Convolutional Neural Networks (CNNs), the generated …

Blind image inpainting aims to repair damaged parts of the image without prior knowledge. It
is a challenging problem due to difficult to infer the background of the damaged area …

Image inpainting represents a fundamental task in computer vision, primarily focusing on the
generation of missing content within an image to restore its integrity and aesthetics. Existing …