3 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing
Yadong Qu, Yuxin Wang, Bangbang Zhou +3
Existing scene text recognition (STR) methods struggle to recognize challenging texts, especially for artistic and severely distorted characters. The limitation lies in the insuffi…
Leveraging Text Localization for Scene Text Removal via Text-aware Masked Image Modeling
Zixiao Wang, Hongtao Xie, YuXin Wang +3
Existing scene text removal (STR) task suffers from insufficient training data due to the expensive pixel-level labeling. In this paper, we aim to address this issue by introducing…
Focus on the Whole Character: Discriminative Character Modeling for Scene Text Recognition
Bangbang Zhou, Yadong Qu, Zixiao Wang +3
Recently, scene text recognition (STR) models have shown significant performance improvements. However, existing models still encounter difficulties in recognizing challenging text…
Self-Supervised Pre-training with Symmetric Superimposition Modeling for Scene Text Recognition
Zuan Gao, Yuxin Wang, Yadong Qu +4
In text recognition, self-supervised pre-training emerges as a good solution to reduce dependence on expansive annotated real data. Previous studies primarily focus on local visual…
Symmetrical Linguistic Feature Distillation with CLIP for Scene Text Recognition
Zixiao Wang, Hongtao Xie, Yuxin Wang +3
In this paper, we explore the potential of the Contrastive Language-Image Pretraining (CLIP) model in scene text recognition (STR), and establish a novel Symmetrical Linguistic Fea…