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- Unified Networking Lab Images Download Free
- Unified Networking Solutions Inc
- Unified Networking Lab Download
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A curated list of resources dedicated to scene text localization and recognition. Any suggestions and pull requests are welcome.
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Papers & Code
Unified Networking Lab Images Download Free
Overview
- [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
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Visual Geometry Group, University of Oxford
- [2016-IJCV, M. Jaderberg] Reading Text in the Wild with Convolutional Neural Networks
paper
demo
homepage
- [2016-CVPR, A Gupta] Synthetic Data for Text Localisation in Natural Images
paper
code
data
- [2015-ICLR, M. Jaderberg] Deep structured output learning for unconstrained text recognition
paper
- [2015-D.Phil Thesis, M. Jaderberg] Deep Learning for Text Spotting
paper
- [2014-ECCV, M. Jaderberg] Deep Features for Text Spotting
paper
code
model
GitXiv
- [2014-NIPS, M. Jaderberg] Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
paper
homepage
model
CUHK & SIAT
Free and premium stock images of Communications and networking.We have thousands of royalty free stock images for instant download. Nov 3, 2016 - Posts about Unified Networking Labs written by layeredsecurity. NOTE: You need to download and install the different images you want to. Supported images Qemu image namings HowTo's HowTo's Video EVE-NG Pro Cookbook Eve-NG upgrade. - Improved lab loading speed. Multivendor network emulation software that empowers network and security professionals with huge opportunities in the networking world. Clientless management options will allow EVE-NG PRO to be as the best choice.
- [2016-arXiv] Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network
paper
- [2016-AAAI] Reading Scene Text in Deep Convolutional Sequences
paper
- [2016-TIP] Text-Attentional Convolutional Neural Networks for Scene Text Detection
paper
- [2014-ECCV] Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees
paper
Downloads EVE-NG Professionnal EVE-NG Community Windows Client Side. Supported images Qemu image namings HowTo's HowTo's Video EVE-NG Pro Cookbook Eve-NG upgrade. Interaction with real network fully supported; simultaneous lab instances. Unetlab has the lowest Google pagerank and bad results in terms of Yandex topical citation index. We found that Unetlab.com is poorly ‘socialized’ in respect to any social network. According to Siteadvisor and Google safe browsing analytics, Unetlab.com is quite a safe domain with no visitor reviews.
Media and Communication Lab, HUST
- [2016-CVPR] Robust scene text recognition with automatic rectification
paper
- [2016-CVPR] Multi-oriented text detection with fully convolutional networks
paper
- [2015-CoRR] An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
paper
code
github
AI Lab, Stanford
Unified Networking Solutions Inc
- [2012-ICPR, Wang] End-to-End Text Recognition with Convolutional Neural Networks
paper
code
SVHN Dataset
- [2012-PhD thesis, David Wu] End-to-End Text Recognition with Convolutional Neural Networks
paper
Others
- [2018-CVPR] FOTS: Fast Oriented Text Spotting With a Unified Network
paper
- [2018-IJCAI] IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection
paper
- [2018-AAAI] PixelLink: Detecting Scene Text via Instance Segmentation
paper
code
- [2018-AAAI] SEE: Towards Semi-Supervised End-to-End Scene Text Recognition
paper
code
- [2017-arXiv] Fused Text Segmentation Networks for Multi-oriented Scene Text Detection
paper
- [2017-arXiv] WeText: Scene Text Detection under Weak Supervision
paper
- [2017-ICCV] Single Shot Text Detector 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
code
- [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
- [2017-ICCV] Deep TextSpotter: An End-to-End Trainable Scene Text Localization andRecognition Framework
paper
code
- [2016-CVPR] Recursive Recurrent Nets with Attention Modeling for OCR in the Wild
paper
- [2016-arXiv] COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images
paper
- [2016-arXiv] DeepText:A Unified Framework for Text Proposal Generation and Text Detection in Natural Images
paper
- [2015 ICDAR] Object Proposals for Text Extraction in the Wild
paper
code
- [2014-TPAMI] Word Spotting and Recognition with Embedded Attributes
paper
homepage
code
Unified Networking Lab Download
Datasets
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MLT 2017
2017
- 7200 training, 1800 validation images
- Bounding box, text transcription, and script annotations
- Task: text detection, script identification
COCO-Text (Computer Vision Group, Cornell)
2016
- 63,686 images, 173,589 text instances, 3 fine-grained text attributes.
- Task: text location and recognition
Synthetic Word Dataset (Oxford, VGG)
2014
- 9 million images covering 90k English words
- Task: text recognition, segmentation
IIIT 5K-Words
2012
- 5000 images from Scene Texts and born-digital (2k training and 3k testing images)
- Each image is a cropped word image of scene text with case-insensitive labels
- Task: text recognition
StanfordSynth(Stanford, AI Group)
2012
- Small single-character images of 62 characters (0-9, a-z, A-Z)
- Task: text recognition
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, segmantation and recognition
Chars74k
2009
- Over 74K images from natural images, as well as a set of synthetically generated characters
- Small single-character images of 62 characters (0-9, a-z, A-Z)
- Task: text recognition
ICDAR Benchmark Datasets
Dataset | Discription | Competition Paper |
---|---|---|
ICDAR 2015 | 1000 training images and 500 testing images | paper |
ICDAR 2013 | 229 training images and 233 testing images | paper |
ICDAR 2011 | 229 training images and 255 testing images | paper |
ICDAR 2005 | 1001 training images and 489 testing images | paper |
ICDAR 2003 | 181 training images and 251 testing images(word level and character level) | paper |