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Found 7 papers, 6 papers with code
Cross-Lingual Learning in Multilingual Scene Text Recognition
We aim to find the condition that exploits knowledge from high-resource languages for improving performance in low-resource languages.
COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts
To encourage research on this topic, we provide a novel comic onomatopoeia dataset (COO), which consists of onomatopoeia texts in Japanese comics.
What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels
To the best of our knowledge, this is the first study that 1) shows sufficient performance by only using real labels and 2) introduces semi- and self-supervised methods into STR with fewer labels.
Character Region Attention For Text Spotting
This architecture is formed by utilizing detection outputs in the recognizer and propagating the recognition loss through the detection stage.
CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks
We believe that our metrics can play a key role in developing and analyzing state-of-the-art text detection and recognition methods.
On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention
Scene text recognition (STR) is the task of recognizing character sequences in natural scenes.
Ranked #3 on
Scene Text Recognition
on ICDAR 2003
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
Many new proposals for scene text recognition (STR) models have been introduced in recent years.
Ranked #7 on
Scene Text Recognition
on ICDAR 2003
