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OCR-free Document Understanding Transformer. (arXiv:2111.15664v4 [cs.LG] UPDATED)
Oct. 5, 2022, 1:12 a.m. | Geewook Kim, Teakgyu Hong, Moonbin Yim, Jeongyeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park
cs.LG updates on arXiv.org arxiv.org
Understanding document images (e.g., invoices) is a core but challenging task
since it requires complex functions such as reading text and a holistic
understanding of the document. Current Visual Document Understanding (VDU)
methods outsource the task of reading text to off-the-shelf Optical Character
Recognition (OCR) engines and focus on the understanding task with the OCR
outputs. Although such OCR-based approaches have shown promising performance,
they suffer from 1) high computational costs for using OCR; 2) inflexibility of
OCR models on …
arxiv document understanding free ocr transformer understanding
More from arxiv.org / cs.LG updates on arXiv.org
The Perception-Robustness Tradeoff in Deterministic Image Restoration
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