Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-ocr
https://github.com/AprilYapingZhang/awesome-ocr
- DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting - Transformer/DeepSolo)]
- Text Spotting Transformers - ucsd/TESTR)]
- SwinTextSpotter: Scene Text Spotting via Better Synergy Between Text Detection and Text Recognition
- Towards Weakly-Supervised Text Spotting Using a Multi-Task Transformer
- Detection and Recognition of Text Embedded in Online Images via Neural Context Models - 4110.<br>
- [code
- STN-OCR: A single Neural Network for Text Detection and Text Recognition
- [code
- Deep TextSpotter: An End-to-End Trainable Scene Text Localization and Recognition Framework - 2212.[[code](https://github.com/MichalBusta/DeepTextSpotter)]
- Textproposals: a text-specific selective search algorithm for word spotting in the wild - 74.[[code](https://github.com/lluisgomez/TextProposals)]
- Word spotting and recognition with embedded attributes - 2566.<br>
- [code
- Deep features for text spotting - 528.<br>
- [code
- DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer - k/DPText-DETR)]
- Towards End-to-End Unified Scene Text Detection and Layout Analysis - research-datasets/hiertext)]
- Vision-Language Pre-Training for Boosting Scene Text Detectors
- Few Could Be Better Than All: Feature Sampling and Grouping for Scene Text Detection
- BTS: A Bi-Lingual Benchmark for Text Segmentation in the Wild
- CentripetalText: An Efficient Text Instance Representation for Scene Text Detection
- Mask is all you need: Rethinking mask r-cnn for dense and arbitrary-shaped scene text detection
- Progressive Contour Regression for Arbitrary-Shape Scene Text Detection
- MOST: A Multi-Oriented Scene Text Detector with Localization Refinement
- Fourier contour embedding for arbitrary-shaped text detection
- Self-Attention Based Text Knowledge Mining for Text Detection - SZU/STKM)
- Semantic-Aware Video Text Detection
- Rethinking text segmentation: A novel dataset and a text-specific refinement approach
- code
- Alchemy: Techniques for Rectification Based Irregular Scene Text Recognition
- Character Region Awareness for Text Detection
- Tightness-Aware Evaluation Protocol for Scene Text Detection
- Shape Robust Text Detection With Progressive Scale Expansion Network
- Detecting Curve Text in the Wild: New Dataset and New Solution
- {TextBoxes++}: A Single-Shot Oriented Scene Text Detector}
- Multi-oriented scene text detection via corner localization and region segmentation
- TextBoxes: A Fast Text Detector with a Single Deep Neural Network
- Detecting Oriented Text in Natural Images by Linking Segments
- [code
- EAST: An Efficient and Accurate Scene Text Detector
- [code
- Single shot text detector with regional attention
- [code
- Detecting text in natural image with connectionist text proposal network - 72.<br>
- [code
- Object proposals for text extraction in the wild - 210.[[code]( https://github.com/lluisgomez/TextProposals)]
- Fastext: Efficient unconstrained scene text detector - 1214.[[code](https://github.com/MichalBusta/FASText)]
- Symmetry-based text line detection in natural scenes - 2567.<br>
- [code
- Detecting text in natural scenes with stroke width transform - 2970.<br>
- [code
- Open-Set Text Recognition via Character-Context Decoupling
- Pushing the Performance Limit of Scene Text Recognizer Without Human Annotation
- SimAN: Exploring Self-Supervised Representation Learning of Scene Text via Similarity-Aware Normalization
- 1
- 2
- 3
- 4
- 5 - STET)
- 6
- 7
- 8
- 9
- 10 - 4Paradigm/AutoSTR.git)
- 11
- 12
- 13
- 1
- A Multi-Object Rectified Attention Network for Scene Text Recognition - Luo/MORAN_v2](https://github.com/Canjie-Luo/MORAN_v2)]
- Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
- Attention-based Extraction of Structured Information from Street View Imagery
- [offical - OCR)]
- Reading Scene Text in Deep Convolutional Sequences - 3508.<br>
- [code
- Learning local and global contexts using a convolutional recurrent network model for relation classification in biomedical text - 321.<br>
- [code
- End-to-end interpretation of the french street name signs dataset - 426.<br>
- [code
- High performance offline handwritten chinese character recognition using googlenet and directional feature maps - 850.<br>
- [code
- An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition - 2304.<br>
- offical - [crnn.pytorch](https://github.com/meijieru/crnn.pytorch)】; 【3 - [unfinished](https://github.com/Belval/CRNN)】; 【4 - [crnn.pytorch-chinese](https://github.com/wulivicte/crnn)】; 【5 - [crnn+stn-tf](https://github.com/chengzhang/CRNN)】; 【6 - [lstm+ctc](https://github.com/ilovin/lstm_ctc_ocr)】; 【7 - [ctpn+crnn-merge-cannot-train](https://github.com/bear63/sceneReco)】; 【8 - [crnn-mnist-keras](https://github.com/jamesmf/mnistCRNN)】; 【9 - [crnn-tf](https://github.com/TJCVRS/CRNN_Tensorflow)】; 【10 - [crnn-tf-could-be-better](https://github.com/AimeeKing/crnn-tensorflow)】; 【11 - [crnn.mxnet](https://github.com/novioleo/crnn.mxnet)】; 【12 - [crnn-tf-estimators](https://github.com/solivr/tf-crnn)】; 【13 - [crnn-attention-tf](https://github.com/wushilian/CRNN_Attention_OCR_Chinese)】; 【14 - [crnn.caffe](https://github.com/yalecyu/crnn.caffe)】; 【15 - [chinese.ocr-ctpn+crnn-tf+pytorch](https://github.com/chineseocr/chinese-ocr)】; 【16 - [another.crnn-attentive pooling](https://github.com/desh2608/crnn-relation-classification)】; 【17 - [crnn-tf-music](https://github.com/meetshah1995/crnn-music-genre-classification)】; 【18 - [crnn-tf-developing](https://github.com/wcy940418/CRNN-end-to-end)】; 【19 - [crnn-torch](https://github.com/yisongbetter/crnn)】; 【20 - [crnn-tf-developing](https://github.com/caihaoye16/crnn)】; 【21 - [chinese-ocr-keras](https://github.com/hehongyu1995/chinese-ocr-train)】; 【22 - [crnn-tf-developing](https://github.com/qiaohan/crnn-train-tf)】; 【23 - [ctpn+crnn-cannot-train-7](https://github.com/qq919056489/ScenceRecognition)】; 【24 - [crnn-pytorch](https://github.com/ahmedmazari-dhatim/CRNN-for-sequence-recognition-)】; 【25 - [cnn+lstm+ctc-tf](https://github.com/watsonyanghx/CNN_LSTM_CTC_Tensorflow)】; 【26 - [crnn-tf-resnet](https://github.com/shoaibahmed/CRNN-TF)]】;【27 - [caffe_ocr](https://github.com/senlinuc/caffe_ocr)】
- Aesthetic Text Logo Synthesis via Content-Aware Layout Inferring
- CVPR-2020
- Synthetic data for text localisation in natural images - 2324.<br>
- [offical
- Knowledge Mining With Scene Text for Fine-Grained Recognition
- ViSTA: Vision and Scene Text Aggregation for Cross-Modal Retrieval
- A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-Resolution
- 1
- 2
- LaTr: Layout-Aware Transformer for Scene-Text VQA
- 1
- Syntax-Aware Network for Handwritten Mathematical Expression Recognition
- Neural Collaborative Graph Machines for Table Structure Recognition
- Fourier Document Restoration for Robust Document Dewarping and Recognition
- Revisiting Document Image Dewarping by Grid Regularization
- C
- ACM Computing Surveys-2020 - Text-Recognition)
- Scene text detection and recognition: Recent advances and future trends - 36.
- www.iapr-tc11.org
- tc11.cvc.uab.es
- rrc.cvc.uab.es
- `2017 COCO-Text`
- `2017 DeTEXT`
- `2017 DOST`
- `2017 FSNS`
- `2017 MLT`
- `2017 IEHHR`
- `2011-2015 Born-DIgitalImage`
- `2013-2015 Focused Scene Text`
- `2013-2015 Text in Videos`
- `2015 Incidental Scene Text`
- ICDAR Chinese
- `Chinese Text in the Wild`
- `Total-Text`
- `SCUT_FORU_DB_Release`
- `SynthText in the Wild Dataset`
- `COCO-Text (Computer Vision Group, Cornell)`
- `COCO-Text API`
- `USTB-SV1k`
- `Synthetic Word Dataset (Oxford, VGG)`
- `download`
- `IIIT 5K-Words`
- `download`
- `StanfordSynth(Stanford, AI Group)`
- `download`
- `MSRA Text Detection 500 Database (MSRA-TD500)`
- `OSTD`
- `Traffice Guide Panel Text Dataset,TGPT`
- `Street View Text (SVT)`
- `KAIST Scene_Text Database`
- `Chars74k`
- ICDAR 2015 - library/manual/10735/paper-icon_1150845_tmb.jpg)](http://rrc.cvc.uab.es/files/Robust-Reading-Competition-Karatzas.pdf)|
- ICDAR 2013 - library/manual/10735/paper-icon_1150845_tmb.jpg)](http://dagdata.cvc.uab.es/icdar2013competition/files/icdar2013_competition_report.pdf)|
- ICDAR 2011 - library/manual/10735/paper-icon_1150845_tmb.jpg)](http://www.iapr-tc11.org/archive/icdar2011/fileup/PDF/4520b491.pdf)|
- ICDAR 2005 - library/manual/10735/paper-icon_1150845_tmb.jpg)](http://www.academia.edu/download/30700479/10.1.1.96.4332.pdf)|
- ICDAR 2003 - library/manual/10735/paper-icon_1150845_tmb.jpg)](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.332.3461&rep=rep1&type=pdf)|
Keywords
ocr
6
text-detection
6
scene-text
4
deep-learning
3
end-to-end
2
scene-text-detection
2
text-recognition
2
scene-text-recognition
2
total-text
2
detection
2
tensorflow
2
robust-reading
2
document-analysis
1
psenet
1
icdar2015
1
ctw1500
1
pytorch
1
ocr-detection
1
cvpr2019
1
curved-text
1
craft
1
semi-supervised-learning
1
mxnet
1
convolutional-neural-networks
1
torch7
1
sequence-recognition
1
machine-learning
1
computer-vision
1
text-detection-recognition
1
icdar
1
dataset
1
curve-text
1
opencv
1
c-plusplus
1
id-card
1
ctpn
1
sstd
1
iccv-17
1
text
1
spotting
1
scene
1
aaai
1
object-detection
1