Line Art Colorization

Line art colorization aims to automatically add color to black-and-white line drawings, a task with applications in animation, illustration, and even medical imaging. Recent research focuses on improving color accuracy and consistency, particularly using deep learning models such as diffusion models and generative adversarial networks (GANs), often incorporating attention mechanisms to better capture relationships between line art and reference images or text prompts. These advancements offer significant potential for automating time-consuming manual processes in creative industries and enhancing the visualization of medical data, leading to increased efficiency and improved results.