Text Spotting
45 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.
Benchmarks
These leaderboards are used to track progress in Text Spotting
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Libraries
Use these libraries to find Text Spotting models and implementationsDatasets
Total-Text
ICDAR 2015
SCUT-CTW1500
LSVTD
Most implemented papers
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
aim-uofa/AdelaiDet
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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
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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
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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
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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
Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.
SPTS v2: Single-Point Scene Text Spotting
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
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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.
A Feasible Framework for Arbitrary-Shaped Scene Text Recognition
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
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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.
Open Images V5 Text Annotation and Yet Another Mask Text Spotter
openvinotoolkit/training_extensions
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A large scale human-labeled dataset plays an important role in creating high quality deep learning models.
