Visual analysis of cylinder seal impressions and unwrappings: annotation and automation

Journal article

Cylinder seals are ancient artefacts whose impressions and digital unwrappings contain rich figurative scenes but lack spatial metadata identifying the motifs within them. We first describe the process of manually annotating motifs in a large digital collection of cylinder seal imagery using software tools, and then describe two applications enabled by these annotations. The first application is a quantitative analyses of motif layout and co-occurrence patterns, supported by a bespoke visualisation tool that aggregates motif distributions across seals. In the second application, we investigate the use of deep learning for automating motif detection. Using 2,491 manually annotated examples, we fine tune an EfficientDet object detector to recognise human related motifs (e.g. king, priest, deity, worshipper, dancer) in seal impressions and unwrapping. Our results demonstrate that combining structured manual annotations with modern computer vision tools can significantly enhance the curation, analysis, and accessibility of cylinder seal collections at scale.

Authors: Bampfield, L; Dahl, JL; Dutta, A; Zisserman, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Cuneiform Digital Library Initiative
• Journal: Cuneiform Digital Library Bulletin
• Volume: 2026
• Issue: 2
• Publication date: 2026-05-17
• Acceptance date: 2026-03-29
• ISSN: 1540-8779
• Language: English
• Keywords: cylinder seal unwrapping; object detection; manual annotation; annotation visualisation