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A General Framework for Text Line Detection and Recognition| title | A General Framework for Text Line Detection and Recognition |
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| start_date | 2024/11/15 |
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| schedule | 11h |
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| online | no |
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| location_info | salle A115 & en ligne |
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| summary | In this seminar, I will present a quick overview of my Ph.D research on transfer learning and generalization, followed by a detailed discussion of our recent NeurIPS paper on General Detection-based Text Line Recognition (DTLR). DTLR is a novel approach for recognizing text lines, whether printed or handwritten, across diverse scripts, including Latin, Chinese, and ciphered characters. Most HTR methods have focused on autoregressive decoding, predicting characters one after the other. Our method shows strong results across various scripts, even those typically addressed by specialized techniques. In particular, we achieve state-of-the-art performance for Chinese script recognition on the CASIA v2 dataset and for cipher recognition on the Borg and Copiale datasets. Finally, I will highlight several collaborative applications and extensions of this work with historians. |
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| responsibles | Bawden |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2024/11/14 11:34 UTC |
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