RT Conference Proceedings
T1 On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs
A1 Stoean, Catalin
A1 Bacanin, Nebojsa
A1 Stoean, Ruxandra
A1 Ionescu, Leonard
A1 Alecsa, Cristian
A1 Hotoleanu, Mircea
A1 Atencia-Ruiz, Miguel Alejandro
A1 Joya-Caparrós, Gonzalo
K1 Materiales - Conservación
AB 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 forthe restorers. The present paper thus attempts to put forward a U-Net approach with a perceptual loss for the semantic inpaintingof traditional Romanian vests. Images taken of pieces from the collection of the Oltenia Museum in Craiova, along withsuch images with garments from the Internet, have been given to the deep learning model. The resulting numerical error forinpainting the corrupted parts is adequately low, however the visual similarity still has to be improved by considering furtherpossibilities for finer tuning.
PB SYNACS  Conference Publishing Service (CPS)
YR 2022
FD 2022
LK https://hdl.handle.net/10630/25290
UL https://hdl.handle.net/10630/25290
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026