MIT graduate student Alex Kachkine has developed an innovative AI-based technique to restore damaged paintings in hours, significantly speeding up traditional restoration processes that can take months. His method employs AI-generated polymer films that serve as transparent “masks” with thousands of color-matched regions, allowing conservators to apply them directly to original artworks without permanent alteration. This reversible process is documented digitally, providing future conservators with a clear understanding of the artwork’s restoration history. Kachkine’s inspiration stemmed from observing the backlog of damaged art during a cross-country drive to MIT, where he realized the immense cultural heritage hidden in storage. To illustrate his technique, he restored a 15th-century oil painting with 5,612 damaged areas in just 3.5 hours, offering a solution to the scarcity of skilled conservators needed for traditional restoration methods. His research highlights the potential of technology in art conservation, making previously overlooked artworks accessible once more.
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