mlsanityData to 7 Oct 2026

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild

arXiv 1603.03101 ↗First posted 9 Mar 2016cs.CVcited by 74

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Abstract (arXiv)

We present recursive recurrent neural networks with attention modeling (R2AM) for lexicon-free optical character recognition in natural scene images. The primary advantages of the proposed method are: (1) use of recursive convolutional neural networks (CNNs), which allow for parametrically efficient and effective image feature extraction; (2) an implicitly learned character-level language model, embodied in a recurrent neural network which avoids the need to use N-grams; and (3) the use of a soft-attention mechanism, allowing the model to selectively exploit image features in a coordinated way, and allowing for end-to-end training within a standard backpropagation framework. We validate our method with state-of-the-art performance on challenging benchmark datasets: Street View Text, IIIT5k, ICDAR and Synth90k.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Mar 2016.

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Citing papers per year: 2021: 26; 2022: 19; 2023: 12; 2024: 11; 2025: 3; 2026: 3.

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  1. 2021Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognitioncited by 194
  2. 2022Scene Text Recognition with Permuted Autoregressive Sequence Modelscited by 148
  3. 2021Vision Transformer for Fast and Efficient Scene Text Recognitioncited by 81
  4. 2022Text Spotting Transformerscited by 70
  5. 2021Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Studycited by 52
  6. 2024From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Modelscited by 52
  7. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  8. 2021PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Networkcited by 49
  9. 2021LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignmentcited by 46
  10. 2021PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognitioncited by 41
  11. 2022ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spottingcited by 40
  12. 2021CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognitioncited by 36
38 more
  1. 2022Multi-Granularity Prediction for Scene Text Recognitioncited by 36
  2. 2023CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Modelcited by 30
  3. 2021Primitive Representation Learning for Scene Text Recognitioncited by 28
  4. 2021MetaHTR: Towards Writer-Adaptive Handwritten Text Recognitioncited by 27
  5. 2021Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognitioncited by 24
  6. 2022Levenshtein OCRcited by 24
  7. 2022On the Cross-dataset Generalization in License Plate Recognitioncited by 22
  8. 2021A Multiplexed Network for End-to-End, Multilingual OCRcited by 18
  9. 2021Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillationcited by 17
  10. 2022Seq-UPS: Sequential Uncertainty-aware Pseudo-label Selection for Semi-Supervised Text Recognitioncited by 14
  11. 2024Layout Agnostic Scene Text Image Synthesis with Diffusion Modelscited by 14
  12. 2023LISTER: Neighbor Decoding for Length-Insensitive Scene Text Recognitioncited by 13
  13. 2021Towards the Unseen: Iterative Text Recognition by Distilling from Errorscited by 12
  14. 2023IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text Recognitioncited by 12
  15. 2024Visually Guided Generative Text-Layout Pre-training for Document Intelligencecited by 12
  16. 2024Out of Length Text Recognition with Sub-String Matchingcited by 11
  17. 2023Leveraging Model Fusion for Improved License Plate Recognitioncited by 10
  18. 2023TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognitioncited by 9
  19. 2022Pushing the Performance Limit of Scene Text Recognizer without Human Annotationcited by 7
  20. 2023Multi-Granularity Prediction with Learnable Fusion for Scene Text Recognitioncited by 7
  21. 2023An Empirical Study of Scaling Law for OCRcited by 7
  22. 2024Qalam : A Multimodal LLM for Arabic Optical Character and Handwriting Recognitioncited by 7
  23. 2026Advancing Multinational License Plate Recognition Through Synthetic and Real Data Fusion: A Comprehensive Evaluationcited by 7
  24. 2021Convolutional Neural Networks with Gated Recurrent Connectionscited by 6
  25. 2021Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognitioncited by 6
  26. 2022Transfer Learning for Scene Text Recognition in Indian Languagescited by 6
  27. 2022TRIE++: Towards End-to-End Information Extraction from Visually Rich Documentscited by 6
  28. 2021Digital Peter: Dataset, Competition and Handwriting Recognition Methodscited by 5
  29. 2021I2C2W: Image-to-Character-to-Word Transformers for Accurate Scene Text Recognitioncited by 5
  30. 2021Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spottercited by 5
  31. 2021Data Augmentation for Scene Text Recognitioncited by 5
  32. 2021STRIDE : Scene Text Recognition In-Devicecited by 4
  33. 2024KhmerST: A Low-Resource Khmer Scene Text Detection and Recognition Benchmarkcited by 4
  34. 2022Task Grouping for Multilingual Text Recognitioncited by 3
  35. 2024Decoder Pre-Training with only Text for Scene Text Recognitioncited by 3
  36. 2026Revise: A Framework for Revising OCRed text in Practical Information Systems with Data Contamination Strategycited by 3
  37. 2021Applications of Machine Learning in Document Digitisationcited by 2
  38. 2021Visual Attention in Imaginative Agentscited by 2

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