Orli model streamlines text line detection and ordering

Researchers have developed Orli, an end-to-end model for text line detection and ordering in historical documents. Orli treats the entire process as a single image-to-sequence problem, directly generating text lines in reading order from a page image. Trained on a large, diverse corpus, Orli achieves state-of-the-art performance on line detection and reading order benchmarks, even without dataset-specific training, and can adapt to specialized layouts with fine-tuning. The model's code and weights are publicly available. AI

影响 This model could improve automated analysis of historical documents by handling complex layouts and marginalia more effectively.

排序理由 The cluster contains a new academic paper detailing a novel model and its performance. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

• Benjamin Kiessling

• 论文
• 模型发布

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