Traditional Chinese Synthetic Datasets Verified with Labeled Data for Scene Text Recognition [article]

Yi-Chang Chen, Yu-Chuan Chang, Yen-Cheng Chang, Yi-Ren Yeh
2022 arXiv   pre-print
Scene text recognition (STR) has been widely studied in academia and industry. Training a text recognition model often requires a large amount of labeled data, but data labeling can be difficult, expensive, or time-consuming, especially for Traditional Chinese text recognition. To the best of our knowledge, public datasets for Traditional Chinese text recognition are lacking. This paper presents a framework for a Traditional Chinese synthetic data engine which aims to improve text recognition
more » ... del performance. We generated over 20 million synthetic data and collected over 7,000 manually labeled data TC-STR 7k-word as the benchmark. Experimental results show that a text recognition model can achieve much better accuracy either by training from scratch with our generated synthetic data or by further fine-tuning with TC-STR 7k-word.
arXiv:2111.13327v2 fatcat:ehwyqirzjjcdvabwib4aeew5ru