Cultural Heritage
Overview
Cultural heritage research applies AI to make collections and traditions easier to document, study, preserve, and share. Common approaches include computer vision and OCR for images and manuscripts, satellite change detection for archaeological sites, spectral imaging and 3D reconstruction for fragile objects, and multimodal models for search and interpretation. Knowledge graphs and retrieval-augmented generation connect answers to collection records, while expert annotation and human-in-the-loop systems help keep outputs grounded. Models can perform well on broad recognition tasks but often struggle with fine-grained cultural context, historical reasoning, authenticity, and evidence-based interpretation.
Latest papers
57 papers8 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.