Скачать или смотреть This AI-powered art restoration is 65 times faster than traditional methods

MIT graduate student Alex Kachkine has developed an AI-powered art restoration system that can repair damaged paintings in hours rather than years.

Detailed in a research paper in Nature titled “Physical restoration of a painting with a digitally constructed mask,” the breakthrough method uses deep learning to analyze artwork damage and digitally reconstruct missing sections, then prints restorations onto ultra-thin transparent masks using museum-quality inks.

The masks can be layered over original paintings and completely removed without damage, addressing ethical concerns about permanent alterations.

Working 65 times faster than traditional hand-painting, the system has attracted Italy's Ministry of Culture, which is adapting it for major projects like earthquake-damaged 15th-century frescoes.