Particle.news
Download on the App Store

MIT’s AI-Printed Mask Restores Damaged Paintings in 3.5 Hours

Printed on thin polymer films, the AI-generated masks can be removed without harming the artwork, speeding conservation up to 70 times faster than traditional techniques.

Overview

  • MIT graduate student Alex Kachkine developed the method by scanning a cleaned painting, creating a digital restoration and printing it onto a two-layer polymer mask.
  • In tests on a 15th-century oil painting, the technique infilled over 5,600 damaged regions using 57,000 colours in just 3.5 hours.
  • The thin removable films adhere to flat, varnished canvases and can be peeled off or dissolved with conservation-grade solutions.
  • A digital record of each mask preserves exact restoration details for future conservators and helps maintain fidelity to the artist’s original intent.
  • The approach is most effective on smooth oil paintings and requires conservator oversight to address ethical and stylistic considerations.