Learning-based image inpainting methods have made remarkable progress in recent years.
Nevertheless, these methods still suffer from issues such as blurring, artifacts, and …

The challenge of image generation has been effectively modeled as a problem of structure
priors or transformation. However, existing models have unsatisfactory performance in …

Extracting adequate contextual information is an important aspect of any image inpainting
method. To achieve this, ample image inpainting methods are available that aim to focus on …

Due to the influence of the light source environment during image acquisition or the subject
not fully opening their eyes, there are phenomena such as light spot interference, eyelash or …

The deep rectangling task aims to transform edge-irregular stitched images into
standardised rectangular formats using deep learning. Existing deep rectangling solutions …

Generalised image outpainting is an important and active research topic in computer vision,
which aims to extend appealing content all-side around a given image. Existing state-of-the …

Image inpainting benefits much from the future Internet, but the memory and computational
cost in encoding image features in deep learning methods poses great challenges to this …

Image inpainting is an active area of research in image processing that focuses on
reconstructing damaged or missing parts of an image. The advent of deep learning has …