论文标题

人工智能可以重建古代马赛克吗?

Can Artificial Intelligence Reconstruct Ancient Mosaics?

论文作者

Moral-Andrés, Fernando, Merino-Gómez, Elena, Reviriego, Pedro, Lombardi, Fabrizio

论文摘要

许多古老的马赛克没有到达我们,因为它们被侵蚀,地震,抢劫甚至用作新建筑中的材料摧毁。更糟糕的是,在我们能够恢复的一小部分马赛克中,许多人受损或不完整。因此,马赛克的恢复和重建在保护文化遗产和了解马赛克在古代文化中的作用起着基本作用。传统上,这种重建是手动进行的,最近是使用计算机图形程序,但总是由人类进行。在过去的几年中,人工智能(AI)在文本描述和参考图像的产生中取得了令人印象深刻的进步。诸如DALL-E2之类的最先进的AI工具可以从文本提示中生成高质量的图像,并可以拍摄参考图像来指导该过程。 2022年8月,DALL-E2启动了一个名为“支出”的新功能,该功能将输入作为不完整的图像和文本提示,然后生成完整的图像,填充缺失的零件。在本文中,我们探讨了这种创新技术是否可以用于重建缺少零件的马赛克。因此,使用dall-e2使用并重建了一组古代马赛克。结果有望表明AI能够解释马赛克的关键特征,并能够产生捕获场景本质的重建。但是,在某些情况下,AI无法再现一些细节,几何形式或引入与其他马赛克不一致的元素。这表明,随着未来几年AI图像生成技术的成熟,它可能是镶嵌重建的宝贵工具。

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.

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