Image inpainting has made remarkable progress with recent advances in deep learning.
Popular networks mainly follow an encoder-decoder architecture (sometimes with skip …

Deep learning (DL) has demonstrated its powerful capabilities in the field of image
inpainting, which could produce visually plausible results. Meanwhile, the malicious use of …

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 …

Image inpainting based on generative adversarial networks (GANs) has achieved great
success in producing visually plausible images and plays an important role in many real …

Conventional detectors suffer from performance degradation when dealing with long-tailed
data due to a classification bias towards the majority head categories. In this article, we …

Text-guided image inpainting aims to generate corrupted image patches and obtain a
plausible image based on textual descriptions, considering the relationship between textual …

Thanks to the powerful learning capability, deep neural networks (DNNs) have acquired
broad applications in single image reflection removal. The DNN-based algorithms relax the …

Digitized methodologies in the recent era contribute to various fields of automation that used
to hold different interests and meanings of human life. Buildings with historical significance …

Image segmentation can reveal the semantic structure information in an image, which is
helpful guidance information for image inpainting. Notably, it can help mitigate the artifacts …

Infrared dim and small target detection is a key technology for various detection tasks.
However, due to the lack of shape, texture, and other information, it is a challenging task to …