Recognizing characters from low-resolution (LR) text images poses a
significant challenge due to the information deficiency as well as the noise
and blur in low-quality images. Current solutions for low-resolution text
recognition (LTR) typically rely on a two-stage pipeline that involves
sup
本文提出了一种 Stroke-Aware Scene Text Image Super-Resolution 方法，通过设计规则分解英文字符和数字，设计 Stroke-Focused Module（SFM）以集中于字符的笔画级内部结构，旨在通过预训练文本识别器为位置提供笔画级别的注意力图，并控制所生成的超分辨率图像与高分辨率真实值之间的一致性，从而实现低分辨率场景文本图像识别的目的。