A curated list of papers and resources for scene text detection and recognition
The year when a paper was first published, including ArXiv publications, is used. As a result, there may be cases when a paper was accepted for example to CVPR 2019, but it is listed in year 2018 because it was published in 2018 on ArXiv.
| Table of contents |
|---|
| 1. Scene Text Detection |
| 2. Weakly Supervised Scene Text Detection |
| 3. Scene Text Recognition |
| 4. Other scene text papers |
| 5. Scene Text Survey papers |
- Detecting text in natural scenes with stroke width transform [CVPR 2010] [paper]
- A Method for Text Localization and Recognition in Real-World Images [ACCV 2010] [paper]
- Real-time scene text localization and recognition [CVPR 2012] [paper]
- Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees [ECCV 2014] [paper]
- Symmetry-based text line detection in natural scenes [CVPR 2015] [paper]
- Object proposals for text extraction in the wild [ICDAR 2015] [paper]
- Text-Attentional Convolutional Neural Network for Scene Text Detection [TIP 2016] [paper]
- Text Flow : A Unified Text Detection System in Natural Scene Images [ICCV 2015] [paper]
- Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network [ArXiv] [paper]
- Multi-Oriented Text Detection With Fully Convolutional Networks [CVPR 2016] [paper]
- Scene Text Detection Via Holistic, Multi-Channel Prediction [ArXiv] [paper]
- Detecting Text in Natural Image with Connectionist Text Proposal Network [ECCV 2016] [paper]
- TextBoxes: A Fast Text Detector with a Single Deep Neural Network [AAAI 2017] [paper]
- Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting In The Wild [CVPR 2017] [paper]
- Deep TextSpotter: An End-To-End Trainable Scene Text Localization and Recognition Framework [ICCV 2017] [paper]
- Arbitrary-Oriented Scene Text Detection via Rotation Proposals [TMM 2018] [paper]
- Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection [CVPR 2017] [paper]
- Detecting Oriented Text in Natural Images by Linking Segments [CVPR 2017] [paper]
- Deep Direct Regression for Multi-Oriented Scene Text Detection [ICCV 2017] [paper]
- Cascaded Segmentation-Detection Networks for Word-Level Text Spotting [ArXiv] [paper]
- EAST: An Efficient and Accurate Scene Text Detector [CVPR 2017] [paper]
- WordFence: Text Detection in Natural Images with Border Awareness [ICIP 2017] [paper]
- R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection [ArXiv] [paper]
- WordSup: Exploiting Word Annotations for Character based Text Detection [ICCV 2017] [paper]
- Single Shot Text Detector With Regional Attention [ICCV 2017] [paper]
- Fused Text Segmentation Networks for Multi-oriented Scene Text Detection [ArXiv] [paper]
- Deep Residual Text Detection Network for Scene Text [ICDAR 2017] [paper]
- Feature Enhancement Network: A Refined Scene Text Detector [AAAI 2018] [paper]
- ArbiText: Arbitrary-Oriented Text Detection in Unconstrained Scene [ArXiv] [paper]
- Self-organized Text Detection with Minimal Post-processing via Border Learning [ICCV 2017] [paper]
- PixelLink: Detecting Scene Text via Instance Segmentation [AAAI 2018] [paper]
- FOTS: Fast Oriented Text Spotting With a Unified Network [CVPR 2018] [paper]
- TextBoxes++: A Single-Shot Oriented Scene Text Detector [TIP 2018] [paper]
- Multi-oriented Scene Text Detection via Corner Localization and Region Segmentation [CVPR 2018] [paper]
- An end-to-end TextSpotter with Explicit Alignment and Attention [CVPR 2018] [paper]
- Rotation-Sensitive Regression for Oriented Scene Text Detection [CVPR 2018] [paper]
- Detecting multi-oriented text with corner-based region proposals [Neurocomputing 2019] [paper]
- An Anchor-Free Region Proposal Network for Faster R-CNN based Text Detection Approaches [ArXiv] [paper]
- IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection [IJCAI 2018] [paper]
- Shape Robust Text Detection with Progressive Scale Expansion Network [CVPR 2019] [paper] [paper v2]
- TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes [ECCV 2018] [paper]
- Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes [ECCV 2018] [paper]
- Accurate Scene Text Detection through Border Semantics Awareness and Bootstrapping [ECCV 2018] [paper]
- A New Anchor-Labeling Method For Oriented Text Detection Using Dense Detection Framework [SPL 2018] [paper]
- An Efficient System for Hazy Scene Text Detection using a Deep CNN and Patch-NMS [ICPR 2018] [paper]
- Scene Text Detection with Supervised Pyramid Context Network [AAAI 2019] [paper]
- Pixel-Anchor: A Fast Oriented Scene Text Detector with Combined Networks [ArXiv] [paper]
- Mask R-CNN with Pyramid Attention Network for Scene Text Detection [WACV 2019] [paper]
- TextMountain: Accurate Scene Text Detection via Instance Segmentation [ArXiv] [paper]
- TextField: Learning A Deep Direction Field for Irregular Scene Text Detection [ArXiv] [paper]
- TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network [ACCV 2018] [paper]
- MSR: Multi-Scale Shape Regression for Scene Text Detection [IJCAI 2019] [paper]
- Scene Text Detection with Inception Text Proposal Generation Module [ICMLC 2019] [paper]
- Towards Robust Curve Text Detection with Conditional Spatial Expansion [CVPR 2019] [paper]
- Curve Text Detection with Local Segmentation Network and Curve Connection [ArXiv] [paper]
- Pyramid Mask Text Detector [ArXiv] [paper]
- Tightness-aware Evaluation Protocol for Scene Text Detection [CVPR 2019] [paper]
- Character Region Awareness for Text Detection [CVPR 2019] [paper]
- Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes [CVPR 2019] [paper]
- TextCohesion: Detecting Text for Arbitrary Shapes [ArXiv] [paper]
- Arbitrary Shape Scene Text Detection With Adaptive Text Region Representation [CVPR 2019] [paper]
- Learning Shape-Aware Embedding for Scene Text Detection [CVPR 2019] [paper]
- A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning [ACMMM 2019] [paper]
- Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network [ICCV 2019] [paper]
- Towards Unconstrained End-to-End Text Spotting [ICCV 2019] [paper]
- TextDragon: An End-to-End Framework for Arbitrary Shaped Text Spotting [paper]
- Convolutional Character Networks [ICCV 2019] [paper]
- Attention-Based Extraction of Structured Information from Street View Imagery [ICDAR 2017] [paper]
- WeText: Scene Text Detection under Weak Supervision [ICCV 2017] [paper]
- SEE: Towards Semi-Supervised End-to-End Scene Text Recognition [AAAI 2018] [paper]
- https://github.com/Bartzi/see [Chainer]
- Deep Structured Output Learning for Unconstrained Text Recognition [ICLR 2015] [paper]
- Reading text in the wild with convolutional neural networks [IJCV 2016] [paper]
- Reading Scene Text in Deep Convolutional Sequences [AAAI 2016] [paper]
- An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition [TPAMI 2017] [paper]
- https://github.com/bgshih/crnn [Torch]
- https://github.com/weinman/cnn_lstm_ctc_ocr [TF]
- https://github.com/watsonyanghx/CNN_LSTM_CTC_Tensorflow [TF]
- https://github.com/MaybeShewill-CV/CRNN_Tensorflow [TF]
- https://github.com/meijieru/crnn.pytorch [PyTorch]
- https://github.com/kurapan/CRNN [Keras]
- Recursive Recurrent Nets with Attention Modeling for OCR in the Wild [CVPR 2016] [paper]
- Robust scene text recognition with automatic rectification [CVPR 2016] [paper]
- CNN-N-Gram for Handwriting Word Recognition [CVPR 2016] [paper]
- STAR-Net: A SpaTial Attention Residue Network for Scene Text Recognition [BMVC 2016] [paper]
- STN-OCR: A single Neural Network for Text Detection and Text Recognition [ArXiv] [paper]
- Learning to Read Irregular Text with Attention Mechanisms [IJCAI 2017] [paper]
- Scene Text Recognition with Sliding Convolutional Character Models [ArXiv] [paper]
- Focusing Attention: Towards Accurate Text Recognition in Natural Images [ICCV 2017] [paper]
- AON: Towards Arbitrarily-Oriented Text Recognition [CVPR 2018] [paper]
- Gated Recurrent Convolution Neural Network for OCR [NIPS 2017] [paper]
- Char-Net: A Character-Aware Neural Network for Distorted Scene Text Recognition [AAAI 2018] [paper]
- SqueezedText: A Real-time Scene Text Recognition by Binary Convolutional Encoder-decoder Network [AAAI 2018] [paper]
- Edit Probability for Scene Text Recognition [CVPR 2018] [paper]
- ASTER: An Attentional Scene Text Recognizer with Flexible Rectification [TPAMI 2018] [paper]
- Synthetically Supervised Feature Learning for Scene Text Recognition [ECCV 2018] [paper]
- Scene Text Recognition from Two-Dimensional Perspective [AAAI 2019] [paper]
- ESIR: End-to-end Scene Text Recognition via Iterative Image Rectification [CVPR 2019] [paper]
- A Multi-Object Rectified Attention Network for Scene Text Recognition [Pattern Recognition] [paper]
- A Simple and Robust Convolutional-Attention Network for Irregular Text Recognition [paper]
- Aggregation Cross-Entropy for Sequence Recognition [CVPR 2019][paper]
- Sequence-to-Sequence Domain Adaptation Network for Robust Text Image Recognition [CVPR 2019][paper]
- 2D Attentional Irregular Scene Text Recognizer [ArXiv] [paper]
- Deep Neural Network for Semantic-based Text Recognition in Images [ArXiv] [paper]
- Symmetry-constrained Rectification Network for Scene Text Recognition [ICCV 2019] [paper]
- Rethinking Irregular Scene Text Recognition (ICDAR 2019-ArT) [paper]
- Focus-Enhanced Scene Text Recognition with Deformable Convolutions [ArXiv] [paper]
- https://github.com/Alpaca07/dtr [PyTorch]
- Adaptive Embedding Gate for Attention-Based Scene Text Recognition [ArXiv] [paper]
- Synthetic Data for Text Localisation in Natural Images [CVPR 2016] [paper]
- Scene Text Synthesis for Efficient and Effective Deep Network Training [ArXiv] [paper]
- Scene Text Detection and Recognition: The Deep Learning Era [ArXiv] [paper]
- Scene text detection and recognition with advances in deep learning: a survey [IJDAR 2019] [paper]