The Role of Generative Systems in Historical Photography Management: A Case Study on Catalan Archives
This work addresses the problem of automated photography management for heritage institutions dealing with historical archives in minoritized languages, though it appears incremental in applying existing methods to a new domain.
This research studied how generative systems can help describe historical photographs from Catalan archives, finding that transfer learning approaches based on visual adaptation and linguistic proximity can effectively address the lack of tools for historical corpora in minoritized languages.
The use of image analysis in automated photography management is an increasing trend in heritage institutions. Such tools alleviate the human cost associated with the manual and expensive annotation of new data sources while facilitating fast access to the citizenship through online indexes and search engines. However, available tagging and description tools are usually designed around modern photographs in English, neglecting historical corpora in minoritized languages, each of which exhibits intrinsic particularities. The primary objective of this research is to study the quantitative contribution of generative systems in the description of historical sources. This is done by contextualizing the task of captioning historical photographs from the Catalan archives as a case study. Our findings provide practitioners with tools and directions on transfer learning for captioning models based on visual adaptation and linguistic proximity.