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Text in the Dark: Extremely Low-Light Text Image Enhancement
April 23, 2024, 4:47 a.m. | Che-Tsung Lin, Chun Chet Ng, Zhi Qin Tan, Wan Jun Nah, Xinyu Wang, Jie Long Kew, Pohao Hsu, Shang Hong Lai, Chee Seng Chan, Christopher Zach
cs.CV updates on arXiv.org arxiv.org
Abstract: Extremely low-light text images are common in natural scenes, making scene text detection and recognition challenging. One solution is to enhance these images using low-light image enhancement methods before text extraction. However, previous methods often do not try to particularly address the significance of low-level features, which are crucial for optimal performance on downstream scene text tasks. Further research is also hindered by the lack of extremely low-light text datasets. To address these limitations, we …
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