Sketch Colorization

Sketch colorization aims to automatically generate realistic color images from grayscale sketches, a challenging problem due to the inherent ambiguity in sketch interpretation. Recent research focuses on leveraging diffusion models and generative adversarial networks (GANs), often incorporating reference images or text prompts to guide the colorization process, and exploring techniques like semantic segmentation to improve accuracy. Furthermore, research is actively investigating methods to optimize user interaction in interactive colorization systems, aiming to minimize the number of user-provided color hints needed for effective results. These advancements hold significant potential for improving digital art creation tools and enhancing image editing capabilities.