Text Spotting

52 papers with code • 4 benchmarks • 6 datasets

Text Spotting is the combination of Scene Text Detection and Scene Text Recognition in an end-to-end manner. It is the ability to read natural text in the wild.

Libraries

Use these libraries to find Text Spotting models and implementations

Most implemented papers

ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

aim-uofa/AdelaiDet CVPR 2020

Our contributions are three-fold: 1) For the first time, we adaptively fit arbitrarily-shaped text by a parameterized Bezier curve.

FOTS: Fast Oriented Text Spotting with a Unified Network

jiangxiluning/FOTS.PyTorch CVPR 2018

Incidental scene text spotting is considered one of the most difficult and valuable challenges in the document analysis community.

Visual Re-ranking with Natural Language Understanding for Text Spotting

ahmedssabir/Visual-Semantic-Relatedness-with-Word-Embedding 29 Oct 2018

We propose a post-processing approach to improve scene text recognition accuracy by using occurrence probabilities of words (unigram language model), and the semantic correlation between scene and text.

Semantic Relatedness Based Re-ranker for Text Spotting

ahmedssabir/Semantic-Relatedness-Based-Reranker-for-Text-Spotting IJCNLP 2019

We present a scenario where semantic similarity is not enough, and we devise a neural approach to learn semantic relatedness.

A Bilingual, OpenWorld Video Text Dataset and End-to-end Video Text Spotter with Transformer

weijiawu/transvtspotter 9 Dec 2021

Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.

SPTS v2: Single-Point Scene Text Spotting

shannanyinxiang/spts 4 Jan 2023

Within the context of our SPTS v2 framework, our experiments suggest a potential preference for single-point representation in scene text spotting when compared to other representations.

ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer

mxin262/estextspotter ICCV 2023

To this end, we introduce a new model named Explicit Synergy-based Text Spotting Transformer framework (ESTextSpotter), which achieves explicit synergy by modeling discriminative and interactive features for text detection and recognition within a single decoder.

Bridging the Gap Between End-to-End and Two-Step Text Spotting

mxin262/bridging-text-spotting 6 Apr 2024

Subsequently, we introduce a Bridge that connects the locked detector and recognizer through a zero-initialized neural network.

A Feasible Framework for Arbitrary-Shaped Scene Text Recognition

zhang0jhon/AttentionOCR 10 Dec 2019

Deep learning based methods have achieved surprising progress in Scene Text Recognition (STR), one of classic problems in computer vision.

AE TextSpotter: Learning Visual and Linguistic Representation for Ambiguous Text Spotting

whai362/AE_TextSpotter ECCV 2020

Unlike previous works that merely employed visual features for text detection, this work proposes a novel text spotter, named Ambiguity Eliminating Text Spotter (AE TextSpotter), which learns both visual and linguistic features to significantly reduce ambiguity in text detection.