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.
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.
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.
