  A large number of ancient mosaics have not reached us because they have been
destroyed by erosion, earthquakes, looting or even used as materials in newer
construction. To make things worse, among the small fraction of mosaics that we
have been able to recover, many are damaged or incomplete. Therefore,
restoration and reconstruction of mosaics play a fundamental role to preserve
cultural heritage and to understand the role of mosaics in ancient cultures.
This reconstruction has traditionally been done manually and more recently
using computer graphics programs but always by humans. In the last years,
Artificial Intelligence (AI) has made impressive progress in the generation of
images from text descriptions and reference images. State of the art AI tools
such as DALL-E2 can generate high quality images from text prompts and can take
a reference image to guide the process. In august 2022, DALL-E2 launched a new
feature called outpainting that takes as input an incomplete image and a text
prompt and then generates a complete image filling the missing parts. In this
paper, we explore whether this innovative technology can be used to reconstruct
mosaics with missing parts. Hence a set of ancient mosaics have been used and
reconstructed using DALL-E2; results are promising showing that AI is able to
interpret the key features of the mosaics and is able to produce
reconstructions that capture the essence of the scene. However, in some cases
AI fails to reproduce some details, geometric forms or introduces elements that
are not consistent with the rest of the mosaic. This suggests that as AI image
generation technology matures in the next few years, it could be a valuable
tool for mosaic reconstruction going forward.
