It is impressive when one gets to see a hundreds or thousands years old artefact exhibited in the museum, whose appearance seems to have been untouched by centuries. Its restoration had been in the hands of a multidisciplinary team of experts and it had undergone a series of complex procedures. To this end, computational approaches that can support in deciding the most visually appropriate inpainting for very degraded historical items would be helpful as a second objective opinion for
the restorers. The present paper thus attempts to put forward a U-Net approach with a perceptual loss for the semantic inpainting
of traditional Romanian vests. Images taken of pieces from the collection of the Oltenia Museum in Craiova, along with
such images with garments from the Internet, have been given to the deep learning model. The resulting numerical error for
inpainting the corrupted parts is adequately low, however the visual similarity still has to be improved by considering further
possibilities for finer tuning.
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