The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks
(CNNs) in creating artistic imagery by separating and recombining image content and style …

Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …

Single image super-resolution (SISR) deals with a fundamental problem of upsampling a
low-resolution (LR) image to its high-resolution (HR) version. Last few years have witnessed …

Edge detection technology aims to identify and extract the boundary information of image
pixel mutation, which is a research hotspot in the field of computer vision. This technology …

When glancing at a magazine, or browsing the Internet, we are continuously exposed to
photographs. Despite this overflow of visual information, humans are extremely good at …

Head portraits are popular in traditional painting. Automating portrait painting is challenging
as the human visual system is sensitive to the slightest irregularities in human faces …

This paper surveys the field of nonphotorealistic rendering (NPR), focusing on techniques
for transforming 2D input (images and video) into artistically stylized renderings. We first …

We present an automatic, real-time video and image abstraction framework that abstracts
imagery by modifying the contrast of visually important features, namely luminance and color …

We present a caricature generation framework based on shape and style manipulation
using StyleGAN. Our framework, dubbed StyleCariGAN, automatically creates a realistic and …

Recent extensions to the standard difference-of-Gaussians (DoG) edge detection operator
have rendered it less susceptible to noise and increased its aesthetic appeal. Despite these …