Scene Text Detection
56 papers with code • 9 benchmarks • 11 datasets
Scene Text Detection is a task to detect text regions in the complex background and label them with bounding boxes.
Source: ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
Benchmarks
| Trend | Dataset | Best Model | Paper Title | Paper | Code | Compare |
|---|---|---|---|---|---|---|
|
||||||
|
||||||
|
||||||
|
||||||
|
||||||
|
||||||
|
||||||
|
||||||
|
Datasets
ICDAR 2013
MSRA-TD500
Total-Text
COCO-Text
ICDAR 2015
SCUT-CTW1500
ICDAR 2017
RCTW-17
Chinese Text in the Wild
TextOCR
Greatest papers with code
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency.
Ranked #1 on
Scene Text Detection
on ICDAR 2015
(Accuracy metric)
Real-time Scene Text Detection with Differentiable Binarization
Recently, segmentation-based methods are quite popular in scene text detection, as the segmentation results can more accurately describe scene text of various shapes such as curve text.
Ranked #2 on
Scene Text Detection
on MSRA-TD500
EAST: An Efficient and Accurate Scene Text Detector
PaddlePaddle/PaddleOCR
•
•
CVPR 2017
Previous approaches for scene text detection have already achieved promising performances across various benchmarks.
Ranked #3 on
Scene Text Detection
on COCO-Text
Robust Scene Text Recognition with Automatic Rectification
PaddlePaddle/PaddleOCR
•
•
CVPR 2016
We show that the model is able to recognize several types of irregular text, including perspective text and curved text.
Ranked #7 on
Scene Text Recognition
on ICDAR 2003
Character Region Awareness for Text Detection
JaidedAI/EasyOCR
•
•
CVPR 2019
Scene text detection methods based on neural networks have emerged recently and have shown promising results.
Ranked #1 on
Scene Text Detection
on ICDAR 2013
(Precision metric)
Detecting Text in Natural Image with Connectionist Text Proposal Network
eragonruan/text-detection-ctpn
•
•
We propose a novel Connectionist Text Proposal Network (CTPN) that accurately localizes text lines in natural image.
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images
The goal of COCO-Text is to advance state-of-the-art in text detection and recognition in natural images.
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
Our contributions are three-fold: 1) For the first time, we adaptively fit arbitrarily-shaped text by a parameterized Bezier curve.
Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
open-mmlab/mmocr
•
•
ICCV 2019
Recently, some methods have been proposed to tackle arbitrary-shaped text detection, but they rarely take the speed of the entire pipeline into consideration, which may fall short in practical applications. In this paper, we propose 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.
Ranked #1 on
Scene Text Detection
on MSRA-TD500
Shape Robust Text Detection with Progressive Scale Expansion Network
open-mmlab/mmocr
•
•
CVPR 2019
Due to the fact that there are large geometrical margins among the minimal scale kernels, our method is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.
Ranked #5 on
Scene Text Detection
on SCUT-CTW1500