mlsanityData to 7 Oct 2026

Text Recognition in the Wild: A Survey

arXiv 2005.03492 ↗First posted 7 May 2020cs.CVcited by 29

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Abstract (arXiv)

The history of text can be traced back over thousands of years. Rich and precise semantic information carried by text is important in a wide range of vision-based application scenarios. Therefore, text recognition in natural scenes has been an active research field in computer vision and pattern recognition. In recent years, with the rise and development of deep learning, numerous methods have shown promising in terms of innovation, practicality, and efficiency. 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. In summary, this literature review attempts to present the entire picture of the field of scene text recognition. It provides a comprehensive reference for people entering this field, and could be helpful to inspire future research. Related resources are available at our Github repository: https://github.com/HCIILAB/Scene-Text-Recognition.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 May 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 10; 2023: 4; 2024: 7; 2025: 1; 2026: 1.

29 papers.

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  1. 2022DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spottingcited by 74
  2. 2023Conditional Text Image Generation with Diffusion Modelscited by 57
  3. 2021CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognitioncited by 36
  4. 2022Multi-Granularity Prediction for Scene Text Recognitioncited by 36
  5. 2022Causal Reasoning Meets Visual Representation Learning: A Prospective Studycited by 24
  6. 2022Levenshtein OCRcited by 24
  7. 2022Multimodal Semi-Supervised Learning for Text Recognitioncited by 16
  8. 2024DNTextSpotter: Arbitrary-Shaped Scene Text Spotting via Improved Denoising Trainingcited by 11
  9. 2024Using Large Language Models to Compare Explainable Models for Smart Home Human Activity Recognitioncited by 9
  10. 2022Open-set Text Recognition via Character-Context Decouplingcited by 8
  11. 2023Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognitioncited by 7
  12. 2021Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifierscited by 6
17 more
  1. 2022TRIE++: Towards End-to-End Information Extraction from Visually Rich Documentscited by 6
  2. 2021Data Augmentation for Scene Text Recognitioncited by 5
  3. 2022OmniPrint: A Configurable Printed Character Synthesizercited by 5
  4. 2021STRIDE : Scene Text Recognition In-Devicecited by 4
  5. 2024NAMER: Non-Autoregressive Modeling for Handwritten Mathematical Expression Recognitioncited by 3
  6. 2024Self-Supervised Learning for Text Recognition: A Critical Surveycited by 3
  7. 2024Improving Chinese Character Representation with Formation Treecited by 2
  8. 2022IterVM: Iterative Vision Modeling Module for Scene Text Recognitioncited by 1
  9. 2024The MERIT Dataset: Modelling and Efficiently Rendering Interpretable Transcriptscited by 1
  10. 2021ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessmentcited by 0
  11. 2021Ultra Light OCR Competition Technical Reportcited by 0
  12. 2022Portmanteauing Features for Scene Text Recognitioncited by 0
  13. 2023VALERIAN: Invariant Feature Learning for IMU Sensor-based Human Activity Recognition in the Wildcited by 0
  14. 2023HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolutioncited by 0
  15. 2024ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Modelscited by 0
  16. 2025AI-Powered Data Visualization Platform: An Intelligent Web Application for Automated Dataset Analysiscited by 0
  17. 2026The RealDefocus Benchmark for Defocus Deblurringcited by 0