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Found 6 papers, 3 papers with code
Conditional Text Image Generation with Diffusion Models
Current text recognition systems, including those for handwritten scripts and scene text, have relied heavily on image synthesis and augmentation, since it is difficult to realize real-world complexity and diversity through collecting and annotating enough real text images.
Tag, Copy or Predict: A Unified Weakly-Supervised Learning Framework for Visual Information Extraction using Sequences
Visual information extraction (VIE) has attracted increasing attention in recent years.
Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter
Specifically, we integrate IFA into the two most prevailing text recognition streams (attention-based and CTC-based) and propose attention-guided dense prediction (ADP) and Extended CTC (ExCTC).
Optical Character Recognition
Optical Character Recognition (OCR)
+1
Text Recognition in the Wild: A Survey
This paper aims to (1) summarize the fundamental problems and the state-of-the-art associated with scene text recognition; (2) introduce new insights and ideas; (3) provide a comprehensive review of publicly available resources; (4) point out directions for future work.
Decoupled Attention Network for Text Recognition
To remedy this issue, we propose a decoupled attention network (DAN), which decouples the alignment operation from using historical decoding results.
Ranked #4 on
Scene Text Recognition
on ICDAR 2003
Adaptive Embedding Gate for Attention-Based Scene Text Recognition
Scene text recognition has attracted particular research interest because it is a very challenging problem and has various applications.
