mlsanityData to 7 Oct 2026

Out-of-Vocabulary Challenge Report

arXiv 2209.06717 ↗First posted 14 Sep 2022cs.CVcited by 11

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Abstract (arXiv)

This paper presents final results of the Out-Of-Vocabulary 2022 (OOV) challenge. The OOV contest introduces an important aspect that is not commonly studied by Optical Character Recognition (OCR) models, namely, the recognition of unseen scene text instances at training time. The competition compiles a collection of public scene text datasets comprising of 326,385 images with 4,864,405 scene text instances, thus covering a wide range of data distributions. A new and independent validation and test set is formed with scene text instances that are out of vocabulary at training time. The competition was structured in two tasks, end-to-end and cropped scene text recognition respectively. A thorough analysis of results from baselines and different participants is presented. Interestingly, current state-of-the-art models show a significant performance gap under the newly studied setting. We conclude that the OOV dataset proposed in this challenge will be an essential area to be explored in order to develop scene text models that achieve more robust and generalized predictions.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 33 of its 43 references that are in the map. First posted on arXiv 14 Sep 2022.

Builds on

33 of 43 references.

References · 33

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  10. 2021Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognitioncited by 194
  11. 2019What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysiscited by 191
  12. 2019Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapescited by 171
21 more
  1. 2020ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Networkcited by 170
  2. 2021TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene textcited by 170
  3. 2017Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognitioncited by 161
  4. 2019ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019cited by 138
  5. 2020SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognitioncited by 119
  6. 2021From Two to One: A New Scene Text Recognizer with Visual Language Modeling Networkcited by 97
  7. 2022Towards End-to-End Unified Scene Text Detection and Layout Analysiscited by 96
  8. 2020Sequence-to-Sequence Contrastive Learning for Text Recognitioncited by 70
  9. 2022Text Spotting Transformerscited by 70
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  11. 2018Scene Text Recognition from Two-Dimensional Perspectivecited by 57
  12. 2019Towards Unconstrained End-to-End Text Spottingcited by 57
  13. 2017Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networkscited by 56
  14. 2021Open Images V5 Text Annotation and Yet Another Mask Text Spottercited by 46
  15. 2020Character Region Attention For Text Spottingcited by 42
  16. 2022Towards Weakly-Supervised Text Spotting using a Multi-Task Transformercited by 41
  17. 2020On Vocabulary Reliance in Scene Text Recognitioncited by 38
  18. 2022GLASS: Global to Local Attention for Scene-Text Spottingcited by 34
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  20. 2020Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrievalcited by 10
  21. 2020On Calibration of Scene-Text Recognition Modelscited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 1; 2025: 2; 2026: 1.

11 papers.

  1. 2023Revisiting Scene Text Recognition: A Data Perspectivecited by 45
  2. 2023CLIPTER: Looking at the Bigger Picture in Scene Text Recognitioncited by 16
  3. 2023Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognitioncited by 14
  4. 2023LISTER: Neighbor Decoding for Length-Insensitive Scene Text Recognitioncited by 13
  5. 2023Leveraging Model Fusion for Improved License Plate Recognitioncited by 10
  6. 2023STEP -- Towards Structured Scene-Text Spottingcited by 2
  7. 2024Platypus: A Generalized Specialist Model for Reading Text in Various Formscited by 2
  8. 2025Style Attack Disguise: When Fonts Become a Camouflage for Adversarial Intentcited by 2
  9. 2023Harnessing the Power of Multi-Lingual Datasets for Pre-training: Towards Enhancing Text Spotting Performancecited by 1
  10. 2026TiCLS : Tightly Coupled Language Text Spottercited by 1
  11. 2025CAE: Character-Level Autoencoder for Non-Semantic Relational Data Groupingcited by 0