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ReELFA: A Scene Text Recognizer with Encoded Location and Focused Attention

Qingqing Wang, Wenjing Jia, Xiangjian He, Yue Lu, Michael Blumenstein, Ye Huang, Shujing Lyu
2019 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW)  
To tackle the above problems, in this paper, we propose a scene text Recognizer with Encoded Location and Focused Attention, i.e., ReELFA.  ...  LSTM and attention mechanism have been widely used for scene text recognition.  ...  ACKNOWLEDGMENT This work was supported by China Scholarship Council (No. 201706140138) and Shanghai Natural Science Foundation (No. 19ZR1415900).  ... 
doi:10.1109/icdarw.2019.40084 dblp:conf/icdar/WangJHLBHL19 fatcat:nr7oreiu2fdcrm5q7ppcytkspy

Text Recognition in the Wild: A Survey [article]

Xiaoxue Chen, Lianwen Jin, Yuanzhi Zhu, Canjie Luo, Tianwei Wang
2020 arXiv   pre-print
This paper aims to (1) summarize the fundamental problems and the state-of-the-art associated with scene text recognition; (2) introduce new insights and ideas; (3) provide a comprehensive review of publicly  ...  The history of text can be traced back over thousands of years. Rich and precise semantic information carried by text is important in a wide range of vision-based application scenarios.  ...  Some researchers added extra information to solve this problem by focusing the deviated attention back onto the target areas, such as localization supervision [24] and encoded coordinates [193] .  ... 
arXiv:2005.03492v3 fatcat:rmzmavxylnf6rbp52lje2mrgiy