Orientation-Independent Chinese Text Recognition in Scene Images

التفاصيل البيبلوغرافية
العنوان: Orientation-Independent Chinese Text Recognition in Scene Images
المؤلفون: Yu, Haiyang, Wang, Xiaocong, Li, Bin, Xue, Xiangyang
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition
الوصف: Scene text recognition (STR) has attracted much attention due to its broad applications. The previous works pay more attention to dealing with the recognition of Latin text images with complex backgrounds by introducing language models or other auxiliary networks. Different from Latin texts, many vertical Chinese texts exist in natural scenes, which brings difficulties to current state-of-the-art STR methods. In this paper, we take the first attempt to extract orientation-independent visual features by disentangling content and orientation information of text images, thus recognizing both horizontal and vertical texts robustly in natural scenes. Specifically, we introduce a Character Image Reconstruction Network (CIRN) to recover corresponding printed character images with disentangled content and orientation information. We conduct experiments on a scene dataset for benchmarking Chinese text recognition, and the results demonstrate that the proposed method can indeed improve performance through disentangling content and orientation information. To further validate the effectiveness of our method, we additionally collect a Vertical Chinese Text Recognition (VCTR) dataset. The experimental results show that the proposed method achieves 45.63% improvement on VCTR when introducing CIRN to the baseline model.
Comment: IJCAI 2023
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2309.01081
رقم الأكسشن: edsarx.2309.01081
قاعدة البيانات: arXiv