Convolutional Neural Networks (CNNs) consistently proved state-of-the-art results in image
Super-resolution (SR), representing an exceptional opportunity for the remote sensing field …

This survey presents a comprehensive study on non-photorealistic rendering (NPR). NPR
technique renders 2D input image into abstracted and artistic stylized images. NPR mainly …

Underwater images suffer from serious color distortion and detail loss because of the
wavelength-dependent light absorption and scattering, which seriously influences the …

Climate change is expected to intensify and increase extreme events in the weather cycle.
Since this has a significant impact on various sectors of our life, recent works are concerned …

We present a learning-based approach for image harmonization, which allows for adjusting
the appearance of the foreground to make it compatible with background. We consider …

The virtual inpainting of artworks provides a nondestructive mode of hypothesis
visualization, and it is especially attractive when physical restoration raises too many …

The goal of arbitrary Neural Style Transfer (NST) is to transform a content image into a
different style. Based on the assumption that styles can be represented by global statistics …

The last 50 years have seen an impressive development of mathematical methods for the
analysis and processing of digital images, mostly in the context of photography, biomedical …

Image style transfer aims to blend the content of one image with the style of another. Due to
the limitation of traditional Convolutional Neural Network (CNN) methods in capturing global …

State-of-the-art image style transfer methods have achieved impressive results by using
neural networks. However, neural style transfer (NST) methods either ignore the local details …