EUFCC-340K: A Faceted Hierarchical Dataset for Metadata Annotation in GLAM Collections
<|reference_start|>EUFCC-340K: A Faceted Hierarchical Dataset for Metadata Annotation in GLAM Collections: In this paper, we address the challenges of automatic metadata annotation in the domain of Galleries, Libraries, Archives, and Museums (GLAMs) by introducing a novel dataset, EUFCC340K, collected from the Europeana portal. Comprising over 340,000 images, the EUFCC340K dataset is organized across multiple facets: Materials, Object Types, Disciplines, and Subjects, following a hierarchical structure based on the Art & Architecture Thesaurus (AAT). We developed several baseline models, incorporating multiple heads on a ConvNeXT backbone for multi-label image tagging on these facets, and fine-tuning a CLIP model with our image text pairs. Our experiments to evaluate model robustness and generalization capabilities in two different test scenarios demonstrate the utility of the dataset in improving multi-label classification tools that have the potential to alleviate cataloging tasks in the cultural heritage sector.<|reference_end|>
@article{net2024eufcc-340k:,
    title={EUFCC-340K: A Faceted Hierarchical Dataset for Metadata Annotation in
  GLAM Collections},
    author={Francesc Net, Marc Folia, Pep Casals, Andrew D. Bagdanov, Lluis Gomez},
    journal={arXiv preprint arXiv:2406.02380},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.02380},
    primaryClass={cs.CV}
}