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computer-vision-7

Text Detection

3260 papers • 126 benchmarks • 313 datasets

Detecting the text in the image and localise it using a bounding box. The text can be in any shape and size. We need to localise all such instances of text in the entire image along with bounding box for each word.

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Benchmarks

These leaderboards are used to track progress in text-detection-7

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Dataset

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UrduDoc

UrduDoc

Libraries

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Use these libraries to find text-detection-7 models and implementations

PaddlePaddle/PaddleOCR

8 papers 38,177

Datasets

UrduDoc

Subtasks

No subtasks available.

Most implemented papers

Shape Robust Text Detection With Progressive Scale Expansion Network

Wenhai Wang, Tong Lu, Xiang Li, Jian Yang, Wenbo Hou, Ruo-Ze Liu•Wed Jun 06 2018

A novel Progressive Scale Expansion Network (PSENet) is proposed, which can precisely detect text instances with arbitrary shapes and is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.

695

Content

Introduction Benchmarks Datasets Subtasks Libraries Papers

open-mmlab/mmocr

8 papers 4,045

mindspore-lab/mindocr

5 papers 155

vitae-transformer/vitae-transformer…

4 papers 67

gxym/textbpn-puls-plus

3 papers 156

gxym/textbpn-plus-plus

3 papers 156

JaidedAI/EasyOCR

2 papers 21,796

alibabaresearch/advancedliteratemac…

2 papers 865

hikopensource/davar-lab-ocr

2 papers 705

mxin262/swintextspotter

2 papers 252

0

Character Region Awareness for Text Detection

Sangdoo Yun, Dongyoon Han, Hwalsuk Lee, Youngmin Baek, Bado Lee•Tue Apr 02 2019

A new scene text detection method to effectively detect text area by exploring each character and affinity between characters by exploiting both the given character- level annotations for synthetic images and the estimated character-level ground-truths for real images acquired by the learned interim model.

921 0

EAST: An Efficient and Accurate Scene Text Detector

C. Yao, Shuchang Zhou, Xinyu Zhou, He Wen, Yuzhi Wang, Weiran He, Jiajun Liang•Mon Apr 10 2017

This work proposes a simple yet powerful pipeline that yields fast and accurate text detection in natural scenes, and significantly outperforms state-of-the-art methods in terms of both accuracy and efficiency.

1620 0

ABCNet: Real-Time Scene Text Spotting With Adaptive Bezier-Curve Network

Chunhua Shen, Tong He, Yuliang Liu, Lianwen Jin, Hao Chen, Liangwei Wang•Sun Feb 23 2020

For the first time, a novel BezierAlign layer is designed for extracting accurate convolution features of a text instance with arbitrary shapes, significantly improving the precision compared with previous methods and introducing negligible computation overhead.

385 0

Real-time Scene Text Detection with Differentiable Binarization

C. Yao, X. Bai, Minghui Liao, Zhaoyi Wan, Kai Chen•Tue Nov 19 2019

This paper proposes a module named Differentiable Binarization (DB), which can perform the binarization process in a segmentation network, and validate the performance improvements of DB on five benchmark datasets, which consistently achieves state-of-the-art results, in terms of both detection accuracy and speed.

789 0

Fourier Contour Embedding for Arbitrary-Shaped Text Detection

Wayne Zhang, Lianwen Jin, Lingyu Liang, Yiqin Zhu, Jianyong Chen, Zhuanghui Kuang•Tue Apr 20 2021

Extensive experiments demonstrate that FCE is accurate and robust to fit contours of scene texts even with highly-curved shapes, and also validate the effectiveness and the good generalization of FCENet for arbitrary-shaped text detection.

237 0

FOTS: Fast Oriented Text Spotting with a Unified Network

Y. Qiao, Ding Liang, Junjie Yan, Xuebo Liu, Shipeng Yan, Dagui Chen•Thu Jan 04 2018

This work proposes a unified end-to-end trainable Fast Oriented Text Spotting (FOTS) network for simultaneous detection and recognition, sharing computation and visual information among the two complementary tasks, and introduces RoIRotate to share convolutional features between detection and Recognition.

524 0

Detecting Oriented Text in Natural Images by Linking Segments

Serge J. Belongie, X. Bai, Baoguang Shi•Sat Mar 18 2017

SegLink, an oriented text detection method to decompose text into two locally detectable elements, namely segments and links, achieves an f-measure of 75.0% on the standard ICDAR 2015 Incidental (Challenge 4) benchmark, outperforming the previous best by a large margin.

684 0

Efficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network

Chunhua Shen, Wenhai Wang, Enze Xie, Tong Lu, Gang Yu, Yuhang Zang, Wenjia Wang, Xiaoge Song•Thu Aug 15 2019

This paper proposes an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing.

481 0

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Text Detection | State-of-the-Art