Recent studies in deepfake detection have yielded promising results when the training and
testing face forgeries are from the same dataset. However, the problem remains challenging …

The most image inpainting algorithms often have existed problems such as blurred image,
texture distortion and semantic inaccuracy, and the image inpainting effect is limited for …

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 …

Currently, most image inpainting algorithms based on deep learning cause information loss
when acquiring deep level features. It is not conducive to the image inpainting of texture …

Image completion aims to restore the corrupted regions in an image. One of the most
important challenges in image completion is to find the most appropriate data for replacing …

Abstract The Generative Adversarial Network (GAN) is commonly used for medical image
augmentation, a method to alleviate the data shortage for downstream tasks. However …

Image and video inpainting is a classic problem in computer vision and computer graphics,
aiming to fill in the plausible and realistic content in the missing areas of images and videos …

Blind image inpainting is a crucial restoration task that does not demand additional mask
information to restore the corrupted regions. Yet, it is a very less explored research area due …

Image matching is a fundamental and critical task in various visual applications, such as
Simultaneous Localization and Mapping (SLAM) and image retrieval, which require …

Face inpainting, the technique of restoring missing or damaged regions in facial images, is
pivotal for applications like face recognition in occluded scenarios and image analysis with …