Art Restoration

Art restoration aims to preserve cultural heritage by repairing damaged or deteriorated artworks, leveraging both traditional techniques and increasingly sophisticated digital methods. Current research focuses on developing and refining AI-powered solutions, particularly employing convolutional neural networks (CNNs), diffusion models, and vision transformers, often combined with multi-stage or multi-scale approaches to address diverse degradation types and sizes. These advancements offer automated, efficient alternatives to traditional methods, improving the accuracy and speed of restoration while preserving the original artistic characteristics. The impact extends to broader accessibility of restoration techniques and the preservation of valuable cultural artifacts.