Bounding Box Label Propagation for Re-Annotation of Document Layout Analysis Datasets

arXiv:2606.17644v1 Announce Type: cross Abstract: Datasets in practical document processing scenarios typically grow over time, and their class annotations undergo continuous refinement. This creates significant re-annotation efforts, which are time-consuming and costly. A promising remedy is to re-annotate only a small subset of available documents manually and apply semi-supervised learning techniques that leverage both labelled and unlabelled data. Although there are numerous approaches to tackle this problem for classification, there exists no adaptation for the problem of re-classifying o

Source: arXiv cs.AI — read the full report at the original publisher.

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