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20212026
most citedPERT: A Progressively Region-based Network for Scene Text Removal

6 citations · 8 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2024

How Control Information Influences Multilingual Text Image Generation and Editing?

Boqiang Zhang, Zuan Gao, Yadong Qu +1

Visual text generation has significantly advanced through diffusion models aimed at producing images with readable and realistic text. Recent works primarily use a ControlNet-based…

cs.CV2024

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…

cs.CV2024

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…