The COTe score: A decomposable framework for evaluating Document Layout Analysis models
Document Layout Analysis (DLA) is the process by which a page is parsed into meaningful elements, often using machine learning models. Typically, the quality of a model is judged using general machine vision metrics such as IoU, F1 or mAP. However, these metrics are designed for images that are 2D projections of 3D space, not for the natively 2D imagery of printed media. This discrepancy can result in misleading or uninformative interpretation of model performance. To encourage more robust, comparable, and nuanced DLA, we introduce: The Structural Semantic Unit (SSU), a relational labelling approach that shifts the focus from the physical to the semantic structure of the content; and the ...
| Authors | Jonathan Bourne, Mwiza Simbeye, Ishtar Govia |
|---|---|
| Primary category | cs.CV |
| Published | 13 March 2026 |
| Last updated at source | 1 October 2026 |
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