OCR, Scene-Text-Understanding, Text Recognition

Overview

Scene-Text-Understanding

Survey

  • [2015-PAMI] Text Detection and Recognition in Imagery: A Survey paper
  • [2014-Front.Comput.Sci] Scene Text Detection and Recognition: Recent Advances and Future Trends paper
  • [2020-Arxiv] Text Recognition in the Wild: A surveypaper

Scene Text Detection

  • [2019-CVPR] Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation [paper]
  • [2019-CVPR] A Multitask Network for Localization and Recognition of Text in Images(end-to-end) [paper]
  • [2019-CVPR] AFDM: Handwriting Recognition in Low-resource Scripts using Adversarial Learning(data augmentation) [paper] [code]
  • [2019-CVPR] CRAFT: Character Region Awareness for Text Detection [paper] [code]
  • [2019-CVPR] Data Extraction from Charts via Single Deep Neural Network(*) [paper]
  • [2019-CVPR] E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text [paper]
  • [2019-arXiv] FACLSTM: ConvLSTM with Focused Attention for Scene Text Recognition [paper]
  • [2019-CVPR] Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes [paper]
  • [2019-CVPR] PSENET: Shape Robust Text Detection with Progressive Scale Expansion Network [paper][tensorflow][Pytorch]
  • [2019-CVPR] PMTD: Pyramid Mask Text Detector [paper] [code]
  • [2019-CVPR] Spatial Fusion GAN for Image Synthesis (word Synthesis) [[paper]](https://arxiv.org/abs/1812.05840 [code]
  • [2019-CVPR] Scene Text Detection with Supervised Pyramid Context Network [paper][keras]
  • [2019-arXiv] TextField: Learning A Deep Direction Field for Irregular Scene Text Detection [paper] [code]
  • [2019-CVPR] Typography with Decor: Intelligent Text Style Transfer [paper] [code]
  • [2019-CVPR] TIOU: Tightness-aware Evaluation Protocol for Scene Text Detection(new Evalution tool)[paper] [code]
  • [2019-arXiv] MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition [paper] [code]
  • [2019-CVPR] Scene Text Magnifier [paper]
  • [2018-CVPR] Pixel-Anchor: A Fast Oriented Scene Text Detector with Combined Networks [paper]
  • [2018-ECCV] Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes [paper] [code]
  • [2018-AAAI] PixelLink: Detecting Scene Text via Instance Segmentation [paper] [code]
  • [2018-CVPR] RRPN: Arbitrary-Oriented Scene Text Detection via Rotation Proposals [paper] [code]
  • [2018-CPVR] Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation [Paper]
  • [2018-arxiv] PixelLink: Detecting Scene Text via Instance Segmentation [Paper]
  • [2018-AAAI] SEE: Towards Semi-Supervised End-to-End Scene Text Recognition [Paper]
  • [2018-arxiv] TextBoxes++: A Single-Shot Oriented Scene Text Detector[Paper]
  • [2017-arxiv] Attention-based Extraction of Structured [Paper]
  • [2017-ICCV]Single Shot TextDetector with Regional Attention [Paper]
  • [2017-ICCV]WordSup: Exploiting Word Annotations for Character based Text Detection [Paper]
  • [2017-arXiv]R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection[Paper]
  • [2017-CVPR]EAST: An Efficient and Accurate Scene Text Detector [Paper] [Code]
  • [2017-arXiv]Cascaded Segmentation-Detection Networks for Word-Level Text Spotting[Paper]
  • [2017-arXiv]Deep Direct Regression for Multi-Oriented Scene Text Detection [Paper]
  • [2017-CVPR]Detecting oriented text in natural images by linking segments [Paper]
  • [2017-CVPR]Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection [Paper]
  • [2017-arXiv]Arbitrary-Oriented Scene Text Detection via Rotation Proposals [Paper]
  • [2017-AAAI]TextBoxes: A Fast Text Detector with a Single Deep Neural Network[Paper][Code]
  • [2016-arXiv]Accurate Text Localization in Natural Image with Cascaded Convolutional TextNetwork [Paper]
  • [2016-arXiv]DeepText : A Unified Framework for Text Proposal Generation and Text Detectionin Natural Images [Paper] [Data]
  • [2017-PR]TextProposals: a Text-specific Selective Search Algorithm for Word Spotting in the Wild [paper] [code]
  • [2016-arXiv] Scene Text Detection via Holistic, Multi-Channel Prediction [Paper]
  • [2016-CVPR] CannyText Detector: Fast and Robust Scene Text Localization Algorithm [Paper]
  • [2016-CVPR]Synthetic Data for Text Localisation in Natural Images[Paper] [Data] [Code]
  • [2016-ECCV]Detecting Text in Natural Image with Connectionist Text Proposal Network[Paper] [Demo][Code]
  • [2016-TIP]Text-Attentional Convolutional Neural Networks for Scene Text Detection[Paper]
  • [2016-IJDAR]TextCatcher: a method to detect curved and challenging text in natural scenes[Paper]
  • [2016-CVPR]Multi-oriented text detection with fully convolutional networks[Paper]
  • [2015-TPRMI]Real-time Lexicon-free Scene Text Localization and Recognition
  • [2015-CVPR]Symmetry-Based Text Line Detection in Natural Scenes
  • [2015-ICCV]FASText: Efficient unconstrained scene text detector [Paper] https://github.com/MichalBusta/FASText
  • [2015-D.PhilThesis] Deep Learning for Text Spotting [Paper]
  • [2015 ICDAR]Object Proposals for Text Extraction in the Wild [Paper] https://github.com/lluisgomez/TextProposals
  • [2014-ECCV] Deep Features for Text Spotting [Paper] https://bitbucket.org/jaderberg/eccv2014_textspotting https://bitbucket.org/jaderberg/eccv2014_textspotting http://gitxiv.com/posts/uB4y7QdD5XquEJ69c/deep-features-for-text-spotting
  • [2014-TPAMI] Word Spotting and Recognition with Embedded Attributes [Paper] http://www.cvc.uab.es/~almazan/index/projects/words-att/index.html https://github.com/almazan/watts
  • [2014-TPRMI]Robust Text Detection in Natural Scene Images
  • [2014-ECCV] Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees [Paper]
  • [2013-ICCV] Photo OCR: Reading Text in Uncontrolled Conditions [Paper]
  • [2012-CVPR]Real-time scene text localization and recognition [Paper]
  • [2010-CVPR]Detecting Text in Natural Scenes with Stroke Width Transform [Paper]

Scene Text Recognition

Phd Thesis

  • [2016-PhD Thesis] Context Modeling for Semantic Text Matching and Scene Text Detection [Paper]
  • [2015-PhD Thesis] Deep Learning for Text Spotting [Paper]
  • [2012-PhD thesis] End-to-End Text Recognition with Convolutional Neural Networks [Paper]

Text Detection

  • [2018-arxiv] TextBoxes++: A Single-Shot Oriented Scene Text Detector [Paper]

Dataset

PowerPoint Text Detection and Recognition Dataset 2017

COCO-Text (ComputerVision Group, Cornell) 2016

  • 63,686images, 173,589 text instances, 3 fine-grained text attributes.
  • Task:text location and recognition

COCO-Text API

Synthetic Data for Text Localisation in Natural Image (VGG)2016

  • 800k thousand images
  • 8 million synthetic word instances
  • download

Synthetic Word Dataset (Oxford, VGG) 2014

  • 9million images covering 90k English words
  • Task:text recognition, segmentation
  • download

IIIT 5K-Words 2012

  • 5000images from Scene Texts and born-digital (2k training and 3k testing images)
  • Eachimage is a cropped word image of scene text with case-insensitive labels
  • Task:text recognition
  • download

StanfordSynth(Stanford, AI Group) 2012

  • Small single-character images of 62 characters (0-9, a-z, A-Z)
  • Task:text recognition
  • download

MSRA Text Detection 500 Database(MSRA-TD500) 2012

  • 500 natural images(resolutions of the images vary from 1296x864 to 1920x1280)
  • Chinese,English or mixture of both
  • Task:text detection

Street View Text (SVT) 2010

  • 350 high resolution images (average size 1260 × 860) (100 images for training and 250 images for testing)
  • Only word level bounding boxes are provided with case-insensitive labels
  • Task:text location

KAIST Scene_Text Database 2010

  • 3000 images of indoor and outdoor scenes containing text
  • Korean,English (Number), and Mixed (Korean + English + Number)
  • Task:text location, segmentation and recognition

Chars74k 2009

  • Over 74K images from natural images, as well as a set of synthetically generatedcharacters

  • Smallsingle-character images of 62 characters (0-9, a-z, A-Z)

  • Task:text recognition

  • ICDAR Benchmark Datasets

Dataset Discription Competition Paper
ICDAR 2017 42618 training images and 9837 testing images paper link
ICDAR 2015 1000 training images and 500 testing images paper link
ICDAR 2013 229 training images and 233 testing images paper link
ICDAR 2011 229 training images and 255 testing images paper link
ICDAR 2005 1001 training images and 489 testing images paper link
ICDAR 2003 181 training images and 251 testing images(word level and character level) paper link

Blogs

Online Service

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