Scene Text Detection

91 papers with code • 9 benchmarks • 15 datasets

Scene Text Detection is a computer vision task that involves automatically identifying and localizing text within natural images or videos. The goal of scene text detection is to develop algorithms that can robustly detect and and label text with bounding boxes in uncontrolled and complex environments, such as street signs, billboards, or license plates.

Source: ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection

Libraries

Use these libraries to find Scene Text Detection models and implementations

Most implemented papers

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

whai362/pan_pp.pytorch 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.

TextFuseNet: Scene Text Detection with Richer Fused Features

ying09/TextFuseNet 17 May 2020

More specifically, we propose to perceive texts from three levels of feature representations, i. e., character-, word- and global-level, and then introduce a novel text representation fusion technique to help achieve robust arbitrary text detection.

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.

PixelLink: Detecting Scene Text via Instance Segmentation

ZJULearning/pixel_link 4 Jan 2018

Most state-of-the-art scene text detection algorithms are deep learning based methods that depend on bounding box regression and perform at least two kinds of predictions: text/non-text classification and location regression.

Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion

MhLiao/DB 21 Feb 2022

By incorporating the proposed DB and ASF with the segmentation network, our proposed scene text detector consistently achieves state-of-the-art results, in terms of both detection accuracy and speed, on five standard benchmarks.

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images

xiaofengShi/CHINESE-OCR 26 Jan 2016

The goal of COCO-Text is to advance state-of-the-art in text detection and recognition in natural images.

Arbitrary-Oriented Scene Text Detection via Rotation Proposals

mjq11302010044/RRPN 3 Mar 2017

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images.

STN-OCR: A single Neural Network for Text Detection and Text Recognition

Bartzi/stn-ocr 27 Jul 2017

In contrast to most existing works that consist of multiple deep neural networks and several pre-processing steps we propose to use a single deep neural network that learns to detect and recognize text from natural images in a semi-supervised way.

TextBoxes++: A Single-Shot Oriented Scene Text Detector

MhLiao/TextBoxes_plusplus 9 Jan 2018

In this paper, we present an end-to-end trainable fast scene text detector, named TextBoxes++, which detects arbitrary-oriented scene text with both high accuracy and efficiency in a single network forward pass.

TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes

open-mmlab/mmocr ECCV 2018

Driven by deep neural networks and large scale datasets, scene text detection methods have progressed substantially over the past years, continuously refreshing the performance records on various standard benchmarks.