mlsanityData to 14 Oct 2026

The Role of Generative Systems in Historical Photography Management: A Case Study on Catalan Archives

arXiv 2409.03911 ↗First posted 5 Sep 2024cs.CV cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 21 of its 37 references that are in the map. First posted on arXiv 5 Sep 2024.

Builds on

21 of 37 references.

References · 21

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  4. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  5. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  6. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
  7. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
  8. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  9. 2017Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answeringcited by 1,312
  10. 2014Deep Visual-Semantic Alignments for Generating Image Descriptionscited by 968
  11. 2023A Survey on Multimodal Large Language Modelscited by 909
  12. 2014Show and Tell: A Neural Image Caption Generatorcited by 879
9 more
  1. 2020Beyond English-Centric Multilingual Machine Translationcited by 561
  2. 2017OpenNMT: Open-source Toolkit for Neural Machine Translationcited by 251
  3. 2022Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Datasetcited by 100
  4. 2019Good News, Everyone! Context driven entity-aware captioning for news imagescited by 66
  5. 2019Generalized Data Augmentation for Low-Resource Translationcited by 53
  6. 2017Self-supervised learning of visual features through embedding images into text topic spacescited by 43
  7. 2021Boosting Entity-aware Image Captioning with Multi-modal Knowledge Graphcited by 31
  8. 2022Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipediacited by 10
  9. 2021Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Datacited by 2

Built on by

Not cited yet.