activity
20172022
most citedFocusing Attention: Towards Accurate Text Recognition in Natural Images

584 citations · 635 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2022★ 3 cited

C3-STISR: Scene Text Image Super-resolution with Triple Clues

Minyi Zhao, Miao Wang, Fan Bai +3

Scene text image super-resolution (STISR) has been regarded as an important pre-processing task for text recognition from low-resolution scene text images. Most recent approaches u…

cs.CV2021★ 10 cited

Federated Face Recognition

Fan Bai, Jiaxiang Wu, Pengcheng Shen +2

Face recognition has been extensively studied in computer vision and artificial intelligence communities in recent years. An important issue of face recognition is data privacy, wh…

cs.CV2020

Text Recognition in Real Scenarios with a Few Labeled Samples

Jinghuang Lin, Zhanzhan Cheng, Fan Bai +3

Scene text recognition (STR) is still a hot research topic in computer vision field due to its various applications. Existing works mainly focus on learning a general model with a…

cs.CV2018★ 33 cited

Edit Probability for Scene Text Recognition

Fan Bai, Zhanzhan Cheng, Yi Niu +2

We consider the scene text recognition problem under the attention-based encoder-decoder framework, which is the state of the art. The existing methods usually employ a frame-wise…

cs.CV2017★ 3 cited

AON: Towards Arbitrarily-Oriented Text Recognition

Zhanzhan Cheng, Yangliu Xu, Fan Bai +3

Recognizing text from natural images is a hot research topic in computer vision due to its various applications. Despite the enduring research of several decades on optical charact…

cs.CV2017★ 584 cited

Focusing Attention: Towards Accurate Text Recognition in Natural Images

Zhanzhan Cheng, Fan Bai, Yunlu Xu +3

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state of the art is the attention-based encoder-decoder framework that…

cs.LG2017★ 2 cited

Label Propagation on K-partite Graphs with Heterophily

Dingxiong Deng, Fan Bai, Yiqi Tang +3

In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption. Homophily label propagation (i.e., two connected nodes share sim…